ShopIQ User Manual

1.ShopIQ Overview #

Analytics has become the need of the hour today and is used by the e-commerce leaders for measuring and improving the multichannel digital customer experience. The e-commerce market is evolving and to keep pace with the market demands it is necessary to analyse customer behavior, application performance and usage patterns to improve the digital customer experience.

Even the slightest of information about a customer, order, or the sales can make a huge difference in garnering conversions. ShopIQ app will enable you to use real-time analytics to discover hidden insights and relationships in the online store’s data which can be utilized to enhance the overall business performance and customer experience.

With this app, you can gain actionable insights from 275+ KPIs and charts, predictive models, and enhanced visualization from 25+ dashboards.

You will get comprehensive reports to leverage your business performance by browsing the dashboard. The retailers can also apply analytics to get an overview of the user flow to drive functional enhancements and improve customer experience. Furthermore, here are some of the key modules that make ShopIQ app an ideal choice to analyse your online store:

Interactive Landing Page

The ShopIQ app is equipped with a user-friendly interface and has dashboards that give an in-depth insight about what is going on your online store. You can easily track down the customer journey and use the information for making their experience better every single time they visit your online store.

Apart from that, you can also view the product-related reports such as the cart values, order progress status, popular brand, and many more in real-time. With this app, you can do a complete page analysis of store and determine the pain points that might be causing hindrance in your business.

Dashboards

The dashboards help you to take a look at insights which are often nestled deep within the data such as abandoned carts, orders count, customers who have canceled the order, etc. By using ShopIQ, you can process such information easily and make instant business decisions to boost conversions.

Report notifications

Users of ShopIQ app would be able to receive updates and notification related to their online store through e-mails and API calls. With this feature, you will get timely updates on what is going on your store and receive notifications that you might have defined for keeping you informed frequently.

For instance, you can set the notification for the cancelled orders by setting a notification template and specifying the time period within which you want to be notified along with the notification message. Doing so will help you to keep track of the number of cancelled orders and take business actions as per the need of the hour.

Real-time capabilities

By integrating the ShopIQ app you would be able to keep track of everything that is happening in real-time on your online store. This will enable you to gain regular insights and take instant actions.

Predictive Use Cases

Predicting the behaviour of the customers on your website can be beneficial for the business as you can plan out strategies that would keep them engaged and garner sales. ShopIQ app is equipped with the predictive analytics feature that can be used to determine customer responses or purchases and promote cross-sell opportunities depending on the customer behaviour. You can train predictive models to attract, retain and grow your most profitable customers.

Yes No

1.1.Getting Started with ShopIQ #

How does the app works?

Install the App

Visit the ShopIQ App store to get access to ShopIQ app. Install the app from the platform and sign-in with your login credentials to get started. (See section 1.3 for more)

Visualize

Once the app is successfully set up, the data will start streaming instantly. You can access the functionality on the dashboards for standard visualization and insights. The users just need to initiate a query and choose the charts to study the data points and their comparison. With this, you will be able to keep track of the trends and changes over time.

Analyse

Try out different analysis features on the platform using the streaming data and monitor the customer behavior. Functionalities such as ad-hoc query, predictive analysis, stream aggregation, among others will enable you to act upon real-time data and generate insights that would be beneficial for your business on a long-term basis.

Customize

You can customize the dashboard and add advanced capabilities to deliver user engagement and drive high-value outcomes. By training models, creating charts, and customizing email reports you will be able to analyse the key aspects of your e-commerce business and also share the same with the members of your team.

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1.2.Video Demonstration #

Take a look at the general overview of ShopIQ along with a brief demonstration of the in-app features here:

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1.3.Installing the app #

Users can install the app by following the given steps:

  1. Go to https://www.iqlect.com/ecommerce-analytics
  2. Choose the plan that you want to go with. Currently, there are Basic, Pro, and Enterprise versions of the app available to choose from.
  3. You will be directed to the Sign Up page where you need to fill the basic details as specified.
  4. Once you click on the Sign Up button you will be sent an activation link along with the license of the platform and an offer for 14-day free trial.
  5. When you activate the link, you will be directed to the homepage of the app where you can access the dashboard by clicking on the My apps tab where you will find the ShopIQ app.
Yes No

1.4.Landing Page #

The landing page is the first page that you get to see when you click on the My Apps tab. It contains snapshots of different dashboards from the account. It displays the summarised data of the dashboards in the form of widgets.

The below listed values are indicated on the landing page:

Widget Description
Click Depth Number of page views in “N” sessions.
Recency Index Number of page views in “N” sessions in the last month upon the total number of the sessions.
Duration Index Number of sessions for more than “n” minutes upon the total number of sessions.
Brand Index Number of people who reached to the website directly upon the total number of sessions.
Conversion Index Number of sessions with purchases upon the total number of sessions.
App Overview Displays the total number of streams, dashboards, charts, and actions present in the app.
Visitors Displays the visitor count over a given period of time along with new and returning count.
Orders Displays the total number of orders,cancelled orders, average order values.
Sales Displays the sales made over an hour, day,  and week along with the cancelled orders.
Cart Displays the total number of  abandoned carts, average cart values, and average number of cart items.
Mobile Displays the number of visitors who accessed the website through mobile, total number of sessions created through mobile, and the total number of orders made through mobile.
Active Checkout Display the checkout values for the current day including average number of checkout items.
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1.5.Customer Onboarding Process #

 

IQLECT uses this space to support its customer on various stages while using the e-commerce application ShopIQ. Once a customer signs up, they will need to integrate their website with our platform to start analyzing data that is flowing from both visitor’s (clickstream) perspective and an e-commerce standpoint.

To initiate this, you can connect with our IT/Web developer to be a part of this discussion to help you set up this platform from our end. You can also consult our support team for further assistance whenever there are concerns.

So, how do we get started? Here we go…

Step 1: Once the account is activated, you will be redirected to Sign In page where you need to fill in your credentials as shown below. You can access the dashboard once you are logged in.

Step 2: After you have logged in, you can click on “My Apps” icon on the top right corner of the page, which will take you to the apps page where all the apps that you have installed will be shown.

Once you click on the desired application, it will take you to the landing page of the app which provides an overview of the data in terms of number of streams, dashboards, charts & actions. From here, you can access the app features for better analysis.

Step 3:To integrate ShopIQ analytics in your website/store, Click on “App Settings” link in the left navigation section as shown below.

Note:

  1. E-commerce analytics is mainly based on website client data.
  2. To capture client events on your website you will need to place iqlect javascript code on all pages of your website/store.

Step 4: To get JS/javascript code, scroll down until you find  “Sending Instructions” module, which has several options to choose among the desired programming language. Here, we will be showcasing the method through Javascript for which you need to select JS

You will be able to see the javascript code readily available and all that you have to do is to copy the script and paste it in all the pages of your website (preferably in head tag).

Ex: 

<script type=”text/javascript”>
  var Iqlect = Iqlect || {};var _iqparams = _iqparams || {};var _iqevents = _iqevents || []; var _iqexparams = _iqexparams || {};

——

</script>

After placing the code just before </head> tag, save the file and exit (use: wq to save & exit). To apply the changes on the store, you need to clear cache.

Example for the demo store we have:

rm -rf /var/www/html/site_demostore/system/storage/cache/*

When you have completed the above steps, you will be able to see clickstream data. In case, the data is not being displayed, please cross check the header file script.

Step 5: Once the script is placed in the header file, the next step is to upload the products. 

To upload the products, continue in the “App settings” section where you will find an option to upload the list of products just above the  “Sending Instructions” module. You can also download the sample CSV file to understand how to update the products for flawless experience.

Note: 

Upload the file in CSV format (others formats are not allowed) with corresponding fields mentioned in the page.

How do we check back if the setup is working fine?

This is very simple as all that you have to do is to cross check whether you have placed the script correctly in the area where its supposed to be placed. Once you have verified  this, follow the steps mentioned below:

Step1: Go back to your website and browse couple of pages randomly, does not have to be anything in particular unless you wanted to look into something very specific. This step is important to analyse and see if the app functions well.

Step 2:  Go back to Iqlect platform > Click on “My Apps” link > Click on the respective app from where you wanted to analyse the data. Once done, you will be directed to the landing/Home page of the App.

Step 3: When you are on the home page, check the count in visitors section (count should have been increased with your visit to the website recently, or if there are other visitors browsing on your website, the count will drastically change as all this gets captured in real-time. Similar changes can be seen in other sections as well.) 

If you find that the count is increased or there is a change in the count on the dashboard, then JS/javascript integration is correct and there is no issue.

E- Commerce Feature Integration 

E-commerce-based analysis uses clickstream data to determine the effectiveness of the site as a channel-to-market. It’s concerned with what pages the customer lingers on, the products that a customer is most likely to purchase or is abandoning, whether or not the customer belongs to a loyalty program and uses a coupon code and their preferred mode of payment, etc.

Please follow the below steps for analysis to take place without any issues. There are few parameters which are not mandatory, so in case, you don’t have them then that can be left blank.

We need to set pageType variable in all pages, depending on the page type. 

For example, if the user is in home page, set pageType =’home’

If the user is in product page, set pageType=’productpage’

_iqexparams.pageType = “”; 

 

Example:

In our test store, we have used the code given below to identify the product page. Our product page code contains below HTML (product specific information is in div tag as data attributes)

<div id=”product-product” data-product-id=”40”, data-product-name=”iPhone” data-manufacturer=”Apple” data-product-price=”100” data-category=”mobile”>

….

….

…. 

</div>

 

In product page specific JS code, use this:

 

<script type=”text/javascript”>

if($(‘#product-product’).length > 0) {

    _iqexparams.pageType = “productpage”;

   

    var obj = $(‘#product-product’);

    _iqexparams.product_id = $(obj).attr(‘data-product-id’);

  _iqexparams.product_name = $(obj).attr(‘data-product-name’);

  _iqexparams.brand_name = $(obj).attr(‘data-product-manufacturer’);

  _iqexparams.category = $(obj).attr(‘data-category’);

  _iqexparams.price_per_unit = $(obj).attr(‘data-product-price’);

}

</script>

 

Note: User will need to fill the required fields depending on the website development.

For integrating the e-commerce events like “add to cart”, “checkout” & “orders” there are two ways to write the code. One way is to write all the Iqlect specific functionality in single JS page and include that in all pages, wherever it is required, and call the corresponding method. Another way is to add specific functionality in specific page.

Add to cart:

The product will be added to the cart when you click on  the ‘add to cart’ button. Here, you can call the Iqlect method to send ‘cart information’.

var cartObj = {

‘customer_id’: 1234,

‘cart_token’: 1111,

‘total_items_price’: 1140.00,

‘subtotal_price’: 1154.20,

‘total_price’: 1154.20,

‘discount_code’: ”,

‘total_discount’: 20.00,

‘shipping_charges’: 10.00,

‘products’:[

{

‘product_id’: ‘P1’

‘price’: 100.50,

‘discount’: 0,

‘quantity’: 1

},

{

‘product_id’: ‘P2’,

‘price’: 100.50,

‘discount’: 0,

‘quantity’: 1

}

]

}

Iqlect.add_to_cart(cartObj);

 

Example Method:

The method given below needs to be followed to get the cart information from backend and format data in the required format. After this, the data will be sent to Iqlect. This code needs to be present in the cart page or common js file.

 

<script type=”text/javascript”>

    /* This method will give the cookie value based on the name of the cookie */

function getCookie(name) {

  var value = “; ” + document.cookie;

  var parts = value.split(“; ” + name + “=”);

  if (parts.length == 2) return parts.pop().split(“;”).shift();

}

 

/* This is a helper method. This will give the value by key in an object. Use your own method to extract the data.*/

 

function getDetailsByKey(data, key) {

        var res = “”;

        for(var i=0; i< data.length; i++ ) {

                if(data[i][‘title’].startsWith(key)) {

                        return data[i];

                }

        }

        return res;

}

 

/* This is a helper method to check whether data is empty/undefined/null */

 

function noe(i) {

        return [undefined, null, ”].indexOf(i) > -1;

}

/* This method gets the cart data from backend and formats in the required format and sends it to Iqlect. Here we have used backend API to fetch the cart data. Depending on your website implementation, you will have an opportunity to modify the URL and the below logic */

function sendAddtoCartData() {

     $.ajax({

        url: ‘index.php?route=common/cart/cartinfo’,

        type: ‘get’,

        success: function(json) {

            var obj = {};

            var cart_id = getCookie(‘cart_token’);  /* Getting cart token from cookie */

            var products = json.products;

            obj[‘customer_id’] = customer_id;

            obj[‘cart_token’] = cart_id;

 

            /* Getting the items price, total price, discount etc and assigning to object */

            var subtotal_price = 0;

            var total_price = 0;

            var discount_code = “NONE”;

            var total_discount = 0;

            var shipping_charges = 0;

            var subtotalObj = getDetailsByKey(json.totals, ‘Sub-Total’);

            var totalObj = getDetailsByKey(json.totals, ‘Total’);

            var discountObj = getDetailsByKey(json.totals, ‘Coupon’);

            var shippingObj = getDetailsByKey(json.totals, ‘Flat Shipping Rate’);

 

            if(!noe(subtotalObj)) {

             subtotal_price = subtotalObj[‘value’];

            }

            obj[‘subtotal_price’] = parseFloat(subtotal_price).toFixed(2);

            obj[‘total_items_price’] = parseFloat(subtotal_price).toFixed(2);

            if(!noe(totalObj)) {

             total_price = totalObj[‘value’];

            }

            obj[‘total_price’] = parseFloat(total_price).toFixed(2);

 

            if(!noe(discountObj)) {

                discount_code = discountObj[‘title’];

                total_discount = discountObj[‘value’];

            }

            obj[‘discount_code’] = discount_code;

            obj[‘total_discount’] = total_discount;

 

            if(!noe(shippingObj)) {

             shipping_charges = shippingObj[‘value’];

            }

            obj[‘shipping_charges’] = shipping_charges;

 

            var detail_obj = [];

            for(var i=0; i< products.length; i++){

                detail_obj[i] = {};

                detail_obj[i][‘product_id’] = products[i][‘product_id’];

                detail_obj[i][‘price’] = products[i][‘price’];

                detail_obj[i][‘quantity’] = products[i][‘quantity’];

                detail_obj[i][‘discount’] = products[i][‘discount’] ? products[i][‘discount’] : 0; 

                /* If the product specific discount is there,then we need to pass that value, otherwise send as zero*/                

            }

            obj[‘products’] = detail_obj;

 

            /* Sending the cart data to Iqlect using below method*/

            Iqlect.add_to_cart(obj);

            

        }

   });

}

/* On successful cart addition, we need to call the sendAddtoCartData method. Here we are calling the method on clicking of ‘add to cart’ button to give you an example. */

$(document).ready(function() {

$(‘#button-cart’).on(‘click’, function() {

sendAddtoCartData();

});

});

 

</script>   

Checkout:

After clicking on checkout/proceed to checkout button, user will land on checkout page. Here, we need to call checkout method(which will send the cart information). To send the checkout event, we need to follow the event similar to “add to cart”, only the method name changes as mentioned below.

Use Iqlect.checkout(obj) instead of Iqlect.add_to_cart(obj); 

var checkoutObj = {

‘customer_id’: 1234,

‘cart_token’: 1111,

‘total_items_price’: 1140.00,

‘subtotal_price’: 1154.20,

‘total_price’: 1154.20,

‘discount_code’: ”,

‘total_discount’: 20.00,

‘shipping_charges’: 10.00,

‘products’:[

{

‘product_id’: ‘P1’

‘price’: 100.50,

‘discount’: 0,

‘quantity’: 1

},

{

‘product_id’: ‘P2’,

‘price’: 100.50,

‘discount’: 0,

‘quantity’: 1

}

]

}

Iqlect.checkout(checkoutObj);

Order:

After completing the payment and a successful order, we need to send order details to Iqlect using Iqlect.order_placed(orderObj). This method needs to be called only once. If you call the method on refresh of order success page, it will make one more entry in Iqlect db and then it will be twice the same order.

var orderObj = {

‘customer_id’: 1234,

‘cart_token’: 1111,

‘order_id’: 123,

’email’: ‘abc@gmail.com‘,

‘billing_city’: ‘Banaglore’,

‘billing_country’: ‘India’,

‘billing_state’: ‘Karnataka’,

‘billing_postcode’: ‘560076’,

‘shipping_city’: ‘Bengaluru’,

‘shipping_country’: ‘India’,

‘shipping_state’: ‘Karnataka’,

‘shipping_postcode’: ‘560010’,

‘payment_method’: ‘Net Banking’,

‘gateway’: ‘FREECHARGE’,

‘currency_code’: ‘INR’,

‘total_items_price’: 1140.00,

‘subtotal_price’: 1154.20,

‘total_price’: 1154.20,

‘discount_code’: ”,

‘total_discount’: 20.00,

‘shipping_charges’: 10.00,

‘products’:[

{

‘product_id’: ‘P1’,

‘discount’: 0,

‘price’: 100.50,

‘quantity’: 1

},

{

‘product_id’: ‘P2’,

‘discouont’: 0,

‘price’: 100.50,

‘quantity’: 1

}

]

}

Iqlect.order_placed(orderObj);

Example Method:

function generateOrder(order_details) {

    var order = order_details.order_info;

    var order_data = order_details.order_data;

    var customer_id = order.customer_id;

    var products = order.products;

    var cart_id = getCookie(‘OCSESSID’);

    var obj = {};

    obj[‘customer_id’] = order.customer_id;

    obj[‘cart_token’] = cart_id;

    obj[‘order_id’] = order.order_id;

    obj[’email’] = order.email;

    obj[‘telephone’] = order.telephone;

    obj[‘billing_city’] = order.payment_city;

    obj[‘billing_country’] = order.payment_country;

    obj[‘billing_state’] = order.payment_zone;

    obj[‘billing_postcode’] = order.payment_postcode;

    obj[‘shipping_city’] = order.shipping_city;

    obj[‘shipping_state’] = order.shipping_zone;

    obj[‘shipping_country’] = order.shipping_country;

    obj[‘shipping_postcode’] = order.shipping_postcode;

    obj[‘payment_method’] = order.payment_method;

    obj[‘gateway’] = order_data.payment_method.code;

    obj[‘currency_code’] = order.currency_code;

    obj[‘shipping_charges’] = order_data.shipping_method.cost ? order_data.shipping_method.cost : 0;

    obj[‘total_price’] = order.total;

 

    var dcode = order_data.coupon ? order_data.coupon : “NONE”;

    var detail_obj = [];

    var product_prices = [];

    for(var i=0; i< products.length; i++){

        var itemprice = Number(products[i][‘price’].replace(/[^0-9.-]+/g,””));

        product_prices.push(itemprice*products[i][‘quantity’]);

        detail_obj[i] = {};

        detail_obj[i][‘product_id’] = products[i][‘product_id’];

        detail_obj[i][‘price’] = itemprice;

        detail_obj[i][‘quantity’] = products[i][‘quantity’];

        detail_obj[i][‘discount’] = products[i][‘discount’] ? Number(products[i][‘discount’]) : 0;

 

    }

    var total_item_price = product_prices.reduce((a, b) => Number(a) + Number(b), 0); //array of sum

    obj[‘total_items_price’] = parseFloat(total_item_price).toFixed(2);

    obj[‘subtotal_price’] = parseFloat(total_item_price).toFixed(2);

    obj[‘total_discount’] = parseFloat(((parseFloat(obj[‘subtotal_price’]) + parseFloat(obj[‘shipping_charges’])) – parseFloat(obj[‘total_price’])));

    obj[‘discount_code’] = dcode;

    obj[‘products’] = detail_obj;

Single Page Application (SPA)

A single-page application (SPA) is a web application or web site that works inside a browser and does not require page reloading during use. It can improve the performance of the web site to a significant extent.

So, if your website has been created with the single page application, follow the steps mentioned below along with the steps mentioned above for a hassle-free experience.

Step 1: In this case, window.load & unload will not work while the user is moving from one page to another page. So, to trigger the method manually follows this: In angular/react, statechange (or equivalent to state change method) will trigger on changing the page. You will need to trigger the load event on statechange success. 

OnStageChangeSuccess:

Iqlect.send_data(‘load’);

OnStateunload(find the correct method name):

Iqlect.send_data(‘unload’);               

Yes No

2.Dashboard #

Dashboards are a collection of widgets that give you a quick overview of the reports and metrics you care about most for your e-commerce business. These let you monitor many metrics at once, so you can check the status of your account or see correlations between different reports.

Each of the dashboards comes with its sets of charts and widgets, however, you can create a customised chart by clicking on the Create New Chart option present on the top right corner when you open any of the dashboard. You will then be directed to the Chart feature in the Customize section where you can follow the same steps as given in section 4.3.

Yes No

2.1.Overview #

Overview provides a quick look into the page and visitor activity on your website. Here, you will get to see the information about the sessions, the number of views, along with total sales and other important information related to your online store.

Chart Description
Active Sessions Number of active sessions on the store.
New Customers Number of unique visitors on the store.
Active Checkout Count Number of orders in the checkout stage.
Returning Customers Number of returning customers in the store.
Active Cart Count Number of orders in the cart
Active Cart Value Value of orders in the cart.
Active Order Value Value of the orders over the last 30 minutes.
Site Profiling Contains information about the website such as its connection time, load time, lookup time, response time.
Active Order Count Number of orders over the last 30 minutes.
Active Visitors Number of active visitors in the past 30 minutes.
Active Checkout Value Value of the orders in the checkout stage over the last 30 minutes.
Total Visitors Total number of visitors on the store.
Total Sessions Total number of sessions at a given instance of time.
Conversion Rate Conversion rate on the website

Overview Average

 

Overview Average provides information related to the average values of the order, cancelled orders, cart value, etc.related to your online store.

Chart Description
Average Order Value Average value of the order
Average Cancelled Value Average value of the cancelled order
Average Cart Value Average value of the orders in the cart
Average Checkout Value Average value of the orders at the checkout stage
Average Abandoned Cart Value Average value of the abandoned cart

Overview Total

Overview Total provides information related to the total value of the orders, number of sessions and visitors, along with other information related to your online store.

Chart Description
Total Visitors Number of visitors on the website.
Total Sessions Number of sessions on the website.
Total Cart Count Number of orders in the cart.
Total Cart Value Value of the orders in the cart.
Total Cart Quantity Number of products in the cart
Total Checkout Count Number of orders in the checkout stage.
Total Checkout Value Value of orders in the checkout stage.
Total Order Count Number of orders.
Total Order Value Value of orders.
Total Cancelled Value Value of cancelled order.
Total Bounce Rate Total bounce rate on the website.
Total New Customers Number of new customers on the website.
Total Returning Customers Number of returning customers.
Overall Conversion Overall conversion rate.
Abandoned Cart Count Number of abandoned carts.
Abandoned Cart Value Value of the orders in the abandoned cart.
Abandoned Quantity Number of products in the abandoned cart
Order Progress Includes a table that shows the status of a particular order. The values that are indicated here include cart token, user id, product names, and product id.

 

Yes No

2.2.Product Analysis #

Products analysis shows you the performance of each product that has been sold on your website. You can use these dashboards to help you determine products that were viewed by customers, and whether you need to add new product lines that would make better sales, or whether you should discard certain products.

Chart Description
Products viewed Details of the products that are being viewed by the customers at a given instance of time.
Products in Checkout Details of the products in the checkout stage at a given instance of time.
Products Being Cancelled Details of the cancelled products at a given instance of time.
Products Abandoned Details of the abandoned products at a given instance of time.
Total Products Viewed Number of products viewed at a given instance of time.
Total Products Sold Number of sold products at a given instance of time.
Total Products Abandoned Number of abandoned products at a given instance of time.
Total Products Cancelled Number of cancelled products at a given instance of time.
Average Count of Products Sold Average number of sold products.
Average Cancellation Value Average value of the cancelled products.
Average Product Abandoned Average number of abandoned products
Average Sales Per Product Average sales made by every product.
Total Cancelled Products Number of cancelled products.
Yes No

2.3.Order Analysis #

Order analysis dashboard shows the status of orders for your e-commerce website. You can use charts provided in this report to see the active order count, tax value, shipping charges related to an order during the selected time period. This dashboard can help you determine the times when the order count is the greatest and least, and whether there are any buying patterns for the orders.

Chart

Description

Active Order Count

Number of placed orders in the last 30 minutes.

Active Order Value

Value of the placed orders in the last 30 minutes.

Active Quantity

Number of items present in the placed orders in the last 30 minutes.

Active Cancelled Value

Value of the cancelled orders over the last 30 minutes.

Active Cancelled Count

Number of cancelled orders in the last 30 minutes.

Active Tax Value

Tax applicable on orders over the last 30 minutes.

Active Shipping Charges

Shipping charges of the orders over the last 30 minutes.

 

Order Analysis Average

 

Order analysis dashboard shows the average status of orders on your e-commerce website. The following widgets will appear on the right side of the page when you click on this dashboard:

Chart

Description

Average Quantity

Average number of products in a particular order.

Average Order Value

Average value of orders at a given instance.

Average Cancelled Value

Average value of cancelled orders at a given instance.

Average Shipping Charges

Average shipping charges on all orders at a given instance.

Average Tax

Average tax levied on all orders at a given instance.

Average Discount

Average discount applicable on all orders at a given instance.

 

Order Analysis Total

 

Order analysis dashboard shows the average status of orders on your e-commerce website. The following widgets will appear on the right side of the page when you click on this dashboard:

Chart

Description

Total Order Value

Total value of the orders

Total Quantity

Total number of products in the order

Total Cancelled Amount

Total amount of cancelled orders

Total tax

Total tax applicable on the orders

Total Shipping Charges

Total shipping charges applicable on the orders

Total Discount

Total tax applicable on the orders

Total Order Count

Total number of placed orders

 

Checkout Analysis

 

The Checkouts analysis dashboard shows the number of times visitors initiated a checkout event for the products they placed in a shopping cart on your website for a given time period. You will be able to see information about the products that are present in the checkout stage along with total value of cart in the checkout stage.

Chart

Description

Number of Customers in Checkout

Number of customers in the checkout stage

Active Checkouts

Number of orders in the checkout stage over the last 30 minutes

Total Checkout Value

Total value of orders in the checkout stage

Active Checkout Value

Value of orders in the checkout stage over last 30 minutes

Average Checkout

Average value of orders in the checkout stage

Active Checkout Quantity

Number of products in the checkout stage over last 30 minutes

Total Checkout Quantity

Total number of products in the checkout stage

Checkout by Price Range

Price of products in the checkout stage

Average Checkout Value

Average value of the orders in the checkout stage

Popular Products by Checkout

Products that reached to the checkout stage most number of times

Orders Funnel

Shows the number of items at different stages of checkout along with total number of items that were placed or cancelled.

Cart Analysis

The cart analysis provides a comprehensive view of the products in the cart along with the status of the order. After launching it, the following widgets will appear on the right hand side of the page:

Chart

Description

Active Cart Value

Value of the cart in the last 30 minutes.

Active Cart Count

Number of orders in the cart over the last 30 minutes.

Total Cart Count

Total number of carts at a given instance.

Total Cart Value

Total value of the cart at a given instance.

Average Cart Value

Average value of the cart at a given instance.

Active Cart Quantity

Number of items in the cart over the last 30 minutes.

Total Cart Quantity

Total number of items in the cart at a given instance.

Average Cart Quantity

Average number of items in the cart at a given instance.

Order Analysis by Discount

This dashboard provides a view of the orders along with the discount that is applicable on the order. After launching it, the following widgets will appear on the right hand side of the page:

Chart

Description

Total Sessions

Total number of sessions.

Total Sessions Where Code Shown

Total number of sessions on which discount code is applicable.

Total Orders with Shown Code

Total number of orders on which discount code is applicable.

Orders Without Discount Code

Number of order on which the discount code is not applicable

Total Sales by Discount Code

Total sales made on the items with discount code.

Total Orders by Discount Code

Total number of orders with applicable discount code.

Order Analysis by Cancelled  

This dashboard provides information related to the cancelled orders. After launching it, the following widgets will appear on the right hand side of the page:

Chart

Description

Cancelled Orders

Total number of cancelled orders

Cancelled Order Details

Details of the cancelled order including the total price, discount, payment type, etc.

Cancelled Products by Category

Details of the category to which the cancelled product belongs.

Cancelled Products

Details related to the cancelled products including their name, category, and the number of times these were cancelled.

Yes No

2.4.Customers #

The customers dashboard displays the information number of customers that are currently online, the total amount spent by them on the website, along with the number of products that they have purchased. Basically, you get to see the customer behaviour on your website through this dashboard.

Chart Description
New Customers Order Value Value of orders placed by new customers
Returning Customers Order Value Value of orders placed by returning customers
Active Customers Number of active customers over the last 30 minutes.
Active Order Value Value of the order in the last 30 minutes.
Total Customers Total number of customers
Total Order Value Total value of orders placed by the customers
Average Order Value Average value of the orders placed by the customers
Average Quantity Average number of products purchased by the customers
Yes No

2.5.Score Analysis #

Scoring analysis dashboard provides information related to the sessions and the score generated for them.

To initiate scoring analysis you will need to follow these steps:

  1. Go to the visitor dashboard and click on any of the session ID that is provided for which you want to get the score details.
  2. You will be directed to the scoring analysis page where you need to click on the Scoring analysis icon present on the top of the page.

At last, the following widgets will be visible when you initiate scoring analysis:

Chart

Description

Sessions by Latest Propensity Score

Propensity score generated for the current users

Propensity Score Details (Line Chart)

Details related to fluctuating values of the propensity score till the final score is generated.

Sessions by Avg Propensity Score

Average propensity score generated for the current users

Sessions by Discount Shown

Sessions that have discounts.

Purchased Sessions by Discount Code

Users who purchased products using the discount code

Propensity Score Information (Bar Chart)

Details related to values of the propensity score till the final score is generated.

Product Category Preferred

Category of products preferred by the users

Brands Preferred

Most preferred brands by the customers.

Colors Preferred by Category

Product colors preferred by the customers which belong to a specific category

Size Preferred by Category

Size preferred by the customers belonging to a specific category

 

User Score Analysis

 

This dashboard provides information related to the attributes based on which the  score is generated for the users.

Chart

Description

Time Spent on Website

Time spent by the user on the website

Events on Website

Events that have occurred on the website

Items in Cart

Number of items in the cart

Cart Value

Value of the cart at a given instance

User Information

Information related to the user including

Number of Times Added to Cart

Number of times the user added products to the cart

Number of Times Removed from Cart

Number of times the user removed products from the cart

Codes Shown

Users that have discounts.

Total Products Viewed

Number of products viewed by the user

Propensity Score Details

Details related to the propensity score generated for a user

Total Events

Total number of events on the website

Event Details

Details related to the events on the website

Review Clicks

Clicks generated while reviewing a product

Total Discount Pop Ups

Number of discount pop Ups.

Page Scroll Events

Number of page scroll events on the website

Total Thumbnail Pop Ups

Number of people who clicked in the thumbnails.

Total Recommendation Clicks

Users who viewed products based on recommendation

Add to Cart Events

Number of add to cart events

Total Removals from Cart

Number of remove from cart events

Pages with Event Count

Number of pages on which events were generated

Traffic Flow in a Session

Flow of user traffic during a particular session

 

User Analysis

 

This dashboard provides information related to the user activity on the online store.

Chart

Description

Time Spent on Website

Time spent by the user on the website

Page Views

Total number of page views

Total Products Viewed

Total number of products viewed by the users

Codes Shown

Discounts codes used by the visitors

Events on Website

Number of events on the website

Signed in Status

Whether a user has signed in or not

New User

Number of new users on the website

Items in Cart

Number of items in the cart

Page Views

Number of page views at a given instance of time

Pages Viewed

Number of pages viewed along with the URL.

Products Viewed

Information related to products that were viewed by the user including their price, count, product Id, etc.

Page Events

Information related to page events including the event name, count, position etc.

Abandoned Cart

Information related to the abandoned cart which includes the product count, session ID, total price of items, etc.

Cart Quantity

Number of carts at a given instance of time

Yes No

2.6.Mobile #

The mobile dashboard displays the activity of the customers who reached the website through mobile. The following widgets will get displayed when you click on this dashboard:

Chart

Description

Page Views

Number of page views through mobile.

Visitors

Number of visitors who reached the website through mobile.

Sessions

Number of sessions through mobile

Stats by Device Manufacturer

Shows the details related to the visitors, page views, sessions, and average load time based on the device manufacturer.

Page Views by Browser

Number of page views through the mobile browser

Mobile Vs Non Mobile

Shows the details related to the visitors, page views, sessions, and average load time based on the mobile users and non-mobile users.

Stats by Service Provider

Shows the details related to the visitors, page views, sessions, and average load time based on the service provider.

Stats by Country

Shows the details related to the visitors, page views, sessions, and average load time based on the country.

Stats by OS

Shows the details related to the visitors, page views, sessions, and average load time based on the operating system.

 

Mobile 2

 

Chart

Description

Bounce Rate

Bounce rate of the website

Mobile Views

Number of views on the website through mobile.

Stats by Gender

Shows the details related to the visitors, page views, sessions, and average load time based on the gender of the visitors.

Yes No

2.7.Traffic Flow #

The traffic dashboard shows data related to customer behaviour on the website. It indicates a user’s entire journey on your online store.

Chart Description
Traffic flow Shows the flow of customer traffic on the website at a given instance of time.
Yes No

2.8.Events #

The Events dashboard shows data related to events that were initiated on a specific page of your website. You will also be able to get a view of the events that were generated from a particular device.

Chart Description
Events Count Number of events that occurred on the website
Events by Device Type Number of events that occurred through a specific device
Event Count Across All Sessions Total number of events generated from all sessions
Event Count Per Page Number of events across every website page
Event Details related to an event including name, trigger count, position, etc.
Page Views Vs Events Total number of page views and events at a given period of time.
Yes No

2.9.Visitors #

Visitors dashboard gives you information about your visitors. Using these reports you can see the number of unique visitors belong to, the number of carts they have abandoned, and so forth.

Chart Description
Unique Visitors Number of unique visitors on the website
Active Load Time Time taken by the website to load.
Total Page Views Total number of page views
Average Time Spent Per Visitor Average time spent by each visitor on the website
Bounce Rate Bounce rate on the website (filter not applicable)
Abandoned Checkout Number of orders that were abandoned during the checkout stage
Unique Sessions Number of unique sessions on the website
Abandoned Carts Number of abandoned carts
Session VS Visitor VS Page Views Number of times a page was viewed by a visitor in a given session.
Number of Visits per Page Number of page visits specific to each page
New Vs Returning Count Number of new and returning customers
Visitors by Device Type Number of visitors who accessed the website through a specific device
Bounce Overall Overall bounce rate (filter is applicable on it)
Conversion Rate Overall conversion rate
Average Views Average number of views on the page

Visitors by OS and Network

This dashboard gives you information about your visitors with respect to the operating system and the service provider they have used to access the website.

Chart Description
Page Views Per Session Number of pages viewed during each session
Views by Service Provider Number of page views according to the service provider
Average Time Spent Per Visitor Average time spent by a visitor on the website
Details by Service Provider Details related to the service provider including page views, sessions, visitors, and average load time.

Visitors by Browser

This dashboard gives you information about your visitors with respect to the browser they have used to access the website.

Chart Description
Page Views by Browser (Pie Chart) Number of page views through a specific browser
Page Views by Browser (Line Chart) Number of page views through a specific browser
Load Time by Browser Time taken the browser to load the website
Stats by Browser Shows the details related to the visitors, page views, sessions, and average load time based on the browser used by the visitor
Stats by Browser Version Shows the details related to the visitors, page views, sessions, and average load time based on the browser version used by the visitor

Visitors by Campaign

This dashboard gives you information about your visitors with respect to the campaign through which they reached the website.

Chart Description
Campaign Details Details related to the campaign including the page views, sessions, campaign name, etc.
Details by UTM Source Details related to the UTM source including the page views, sessions, campaign name, etc.
Visitors by Campaign Number of visitors who accessed the online store through campaign
Visitors by UTM Source Number of visitors who accessed the online store through UTM source
Visitors by Channel Number of visitors who accessed the online store through a media channel
Visitors by UTM Medium Number of visitors who accessed the online store through a UTM medium

Visitors by Device

This dashboard gives you information about your visitors with respect to the device they have used to access the website.

Chart Description
Visitor Distribution Distribution of visitors based on the device used by them
Sessions Number of sessions generated from a particular device
Details by Device Type Details related to the device which include its type, average load time, etc.
Details by Manufacturer Details related to the  device manufacturer including the page views, average load time, sessions, etc.
Details by Resolution Details of the device depending on the resolution.
Pages View by Manufacturer Number of page views specific to a particular manufacturer.

Visitors by Geo

This dashboard gives you information about your visitors with respect to their location.

 

Chart Description
Visitor Distribution Map Map showing the distribution of visitors across the world
Country Wise Details Details related to the visitors belonging to a specific country including the number of page views, sessions, as well as the average load time of the website
State Wise Details Details related to the visitors belonging to a specific state, including the number of page views, sessions, as well as the average load time of the website
City Wise Details Details related to the visitors belonging to a specific city including the number of page views, sessions, as well as the average load time of the website
Top Countries by Page Views Countries with the highest number of page views
Top States by Page Views States with the highest number of page views
Top City by Page Views Cities with the highest number of page views
Total Events Count Total number of events generated at a given instance

Visitors by Demographics

This dashboard gives you information about your visitors with respect to their location.

Chart Description
Details by Gender Shows the average load time, page views, number of visitors specific to a gender.
Page Views by Gender Number of page views based on the gender of users
Yes No

2.10.Campaign Analysis #

Campaign analysis provides an overview of the sales that were made  along with the visitors who reached the website through a specific campaign. The information that is generated here will be useful in determining the performance of a marketing campaign and the impact that it has created on the targeted audiences.

Chart

Description

Total Sessions through Campaign

Number of sessions who reached the website through campaign

Total Orders through Campaign

Number of orders placed through campaign

Total Sale through Campaign

Total sales made through campaign

Campaign Details

Indicates the details related to the campaign which include visitors, sessions, page views, and UTM campaign

Sales by Campaign

Indicates the details related to the total orders, price, sessions, the campaign through which sales were made.

Visitors by Campaign

Number of visitors who reached the website through campaign.

Sales by Campaign

Sales made through a campaign.

Details by UTM Source

Details related to the UTM Source including the page views, sessions, visitors, and UTM source.

Sales by Source Per Campaign

Sales made during every campaign through the UTM Source

Visitors by UTM Source

Visitors who reached the website through UTM source.

Sales by UTM Source

Sales made through the UTM Source

Yes No

3.Notification Templates #

Scheduling notifications can help the business teams to get alerts regarding business functionalities and plan out strategies that would be best suited for increasing conversions.

The Notification templates feature helps to achieve this task and enables you to create alerts and notifications that are generated on particular actions that occur on the e-commerce website. You can also keep track of specific activity on your online store as per the specified time.

Yes No

3.1.Adding Notifcation Template #

Follow the below mentioned steps for adding notification templates:

  1. Click on +Add New Notification Template that you will see on the right corner of the window when you launch the Notification Template feature.

2. Provide a name for the notification so that it gets easier for you to recognise it when it shows up.

3. Select the type of users (Can be created by choosing the Group option present on the drop-down list when you click your account name on top right corner of the app window. See section 9.) who will receive the notification.

4. Indicate the time frame within which you want to receive the notifications so that you get updates on a timely basis.

5. Choose where you want to be notified. By default, the setting is available for the Email option.

6. Provide a notification message for the template.

7. Set the priority level for the notification.

8. Provide a tag that acts like a metadata tag and helps in finding messages with a specific theme or content. You can also save the notification as a template by clicking on the checkbox provided.

9. Click Submit.

Once done, the new template will appear at the notification information section where you can also edit it later on.

Yes No

4.Customize #

The Customize tab enables you to train models, create charts, initiate actions for generating alerts and notifications pertaining to a business requirement. With this, you will be able to modify the data visualisation features to suit a particular task.

Yes No

4.1.Streams #

E-commerce websites get a continuous flow of useful data from various sources which can be analysed and utilised for the growth of the business. These data elements are referred to  as Streams that are collected at a destination source over the course of time. The stream is nothing but the set of events belonging to a particular data source typically in time series manner

In the case of ShopIQ App, the destination source is Ampere :https://www.iqlect.com/features.html which is a platform created by IQLECT.

Each stream has a set of attributes that can be user-defined. The information that is collected in a stream can be utilised for creating charts, generate actions, link data sources, along with other functionalities wherever it is applicable.

The Streams Page that you see when you click on the Streams feature contains the list of data streams and derived streams in the system which are primarily related to the customers, orders, products, and page events on your online store. For example, the stream ‘Abandoned_carts’ contains attributes such as total_items_price, price_range, product_names, etc.,that indicate complete information related to this stream.

There are basically two types of streams available on Ampere:

  1. Raw data streams: This is a basic stream with several attributes. Ex: CUSTOMERS.
  2. Derived streams: These are created on an existing stream using following functionalities:
  • Aggregation: Used to perform aggregation operations such as average, max, min, count and cardinality. Ex: Avg of Discounts-Price-Tax-Shipping.
  • Groupby: Performs operations such as average, max, min, count and cardinality with groupby on some attributes:
  • Static: These streams cannot be changed or modified later on. Ex: st_customers.
  • Static aggregation: Performs aggregation operations such as average, max, min, count and cardinality on a static stream. Ex: Abandoned_carts
  • Predictive: Used to apply and store the result of a given training model on a particular stream. Ex: Sessions_scored
  • Complex Event Processing: Used to filter, combine, and correlate streams and to find state based patterns in continuous sliding windowed manner. The patterns identified with CEP are with 100 % confidence.

To create a stream follow the steps given below:

  1. Provide a Stream Name.
  2. Click on Add Attributes. Enter Attribute Name, select Attribute Type, choose if the attribute should be indexed (check the box to enable indexing). Indexing will allow searching of data at a later stage.
  3. Add more attributes if you want (by default a value of 1 is provided). By providing a numerical value in the field, several rows can be added.
  4. Once you have added the required attributes, Click on Done.
  5. Now, you have named the stream as well as the attribute. Along with this, choose an attribute that you want to index for text search. You can then click on Save to create the data stream which will be visible on the stream page on the right side.

The labels and fields associated with the streams are explained below:

Stream name: Name of the stream

Event count: Number of streams that have arrived in the last interval

Status: Shows whether the stream is enabled or disabled

Each stream has four quick launch buttons – Analyze, Visualize, Act, Drill which can be found in the row that contains the streams.

Launch Button Description
Analyze: Takes the user to the aggregation wizard where they can modify the stream as per the requirements.
Visualize: Takes the user to the chart creation wizard where they can modify the stream as per the requirements.
Act on stream:Takes the user to the actions wizard where they can modify the stream as per the requirements.
Drill down process: Initiates drill down process for the stream.
Copy: This feature is available only for the raw data streams. It creates a new stream with similar attributes and structure however the data input will be different in both the cases.

The checkbox ‘Show only data streams’ filters the entire list of streams and displays only the data streams by hiding the derived and/or analytics streams.

Yes No

4.2.Actions #

Notifying the team members regarding a specific entity, say, ‘Cancelled Orders’ can help in taking quick business actions related to user engagement so as to determine reasons behind cancelling an order. This information would help in initiating marketing campaigns for boosting sales.

To initiate such notifications, the Action feature can help in triggering alert/notifications on a specific condition for a data stream. By using actions effectively, you can take corrective measures regarding the business process and share the notifications with the team members.

The Actions page displays the list of actions that are currently available and also allows users to create new action.

The following labels describe the existing actions in the system.

Action name: Refers to the action.

Notification count: Shows how many times the condition has been met in the last interval.

Status: Toggle switch to turn an action on or off.

Copy: Duplicate the action.

Search: User can search an action by providing an action name.

Creating an action is tightly connected with notifications. To create an action provide the following:

1. Provide a label/name for the action that is being created.

2.  An action can be taken on this list of streams provided in the Select Input Data Stream option. It includes regular streams and derived (aggregated, complex) streams. You can choose a stream from the list.

3. You can then Add Condition for the time when you want to get notified. Along with that, this contains the list of conditions under which the action will be triggered.

4. The Action Condition can be defined by indicating these values:

Field Name: The attribute value that will be checked for condition.

Operator: The list of comparative operations to be performed.

Value: The user-defined value against which the field value is to be configured.

Get Notified When: Defines the frequency of occurrence upon which the action is triggered.

7. The group selected under Get Notified At will be notified upon meeting the condition. In case an API endpoint is defined then the API endpoint will be triggered.

 Note:  API endpoint is an optional field to provide an API endpoint that can be triggered in case of the conditions being met.

8. Click Submit to complete.

Upon submission, the new action will be formed in the list of actions.

Yes No

4.3.Chart #

Charts help to visually illustrate the relationships in the data. These can be used to present large amounts of e-commerce data that might be complicated to describe and showcase it in a succinct and readable manner. By using the chart feature provided by IQLECT’s ShopIQ app, the users would be able to determine the pronounced trends and also reveal relations between different variables.

Basically, two categories of charts can be plotted using this feature which include:

Time-series chart: It illustrates data points at successive intervals of time. Plotting this kind of chart can help the end users to identify a trend, or analyze how a key metric changes over time.

 

Snapshot chart: It illustrates the data points at a specific period of time. Plotting this kind of chart can be used to analyse the information generated at a given time.

 

Follow these steps to create a chart:

  1. You will first need to select the type of analysis that you want to perform. The following options can chosen from the drop down list:
    • Normal Analysis: Used to plot regular stream attribute data.
    • Comparative Analysis: Used to plot data trend between two time periods.
    • Trend Analysis: This is similar to normal analysis but it is plotted on the data collected in the past.
    • Cumulative Analysis: Used to plot chart with cumulative data within given intervals.
    • Static Analysis: A snapshot chart can be plotted using this analysis by taking any parameters from the data collected in the past.

Select a query that will be plotted on the chart. The final chart may contain more than one query.

  1. To begin creating a query, select the input stream on which the chart will be created. Depending on the type of attributes in a stream, grouping option for the attribute may be available. The type of chart to be displayed can be selected from the dropdown list of chart types.
  2. Upon selecting the stream, the attribute codes are displayed on the pop-up window.
  3. User may select the attribute that needs to be displayed on the chart. Different attributes types such as integer, string, long and decimal are color-coded.
  4. Dynamic and static filter may also be applied on the chart using the different tabs. A dynamic filter will allow users to filter data at the dashboard. A static filter will filter the data continuously. Users can plot multiple attributes on a single chart by clicking on new attributes.
  5. Provide the labels for X-axis, Y-axis and tooltip for this query. As you add new query, you may add more Y-axis labels.
  6. Add more query if necessary or plot the chart to see the preview.
  7. In order to save the chart, click on +Save Chart.
  8. A window will appear on the right hand side where you can provide details for the chart including the title, subtitle, description.
  9. You can then choose the option of adding the chart to the existing dashboard or can even provide a completely new chart. Choose the dashboard on which you want to plot from the drop down list and click on the Add to Dashboard.

Once done, you will then be able to view this chart on the respective dashboard.

Yes No

4.5.Custom Log #

Data organisation is essential in e-commerce business otherwise it might get difficult to gather useful information related to orders, sales, or customers which in return can affect the overall performance of the business. One solution to it is to consider using rule sets to specify what data to include in the logs, the display order, the conditional logic for filtering which requests are included, and the log file number and names.

The custom log feature can be used for this purpose as it monitors and analyses the custom log files using a data stream.

Follow these steps to create a data stream that can read a custom log:

  1. Provide the path of the custom log location (file location at the data source) > Provide a sample log entry for the custom log > Select the type of delimiter used for the custom log entry. If the delimiter is not listed then add it using ‘Other delimiter’. Similarly if the log entries are more complex, a regular expression for the sample log can be written by choosing ‘Write Regex’.

  2. Click ‘Next’ to continue.

  3. In this step, map the sample log entry with attribute name and code. Provide the necessary inputs.

  4. Provide a name to the output stream and choose if you would like to use the IQLECT agent.

Yes No

4.6.Training #

The process of training a machine learning model involves providing a learning algorithm with training data to learn from. The goal of the algorithm is to take some data with a known relationship and to create a model of those relationships. The model thus trained can be used for predictive analysis that will help in understanding patterns related to customer behaviour.

Here are the  steps to train a model:

  1. Provide a model name.
  2. Select an algorithm that you want to apply on the model and once you are done with this click on + present at the right of the dialog box. Following options can be selected depending on the requirement:
  • Classification – Single Label: A single label may be assigned to each instance of data.
  • Classification – Multi Label:  Multiple labels may be assigned to each instance of data.
  • Regression: It is used to model the relationship between a dependent variable and one or more independent variables.

Attributes that need to be filled for above three streams are as follows:

Attribute

Description

kernel : string, optional (default=’rbf’)

Specifies the kernel type to be used in the algorithm. It must be one of ‘linear’, ‘poly’, ‘rbf’, ‘sigmoid’ or ‘precomputed’. If none is given, ‘rbf’ will be used.

degree : int, optional (default=3)

Degree of the polynomial kernel function (‘poly’). Ignored by all other kernels.

gamma : float, optional (default=1/num_features)

Kernel coefficient for ‘rbf’, ‘poly’ and ‘sigmoid’.

coef0 : float, optional (default=0.0)

Independent term in kernel function. It is only significant in ‘poly’ and ‘sigmoid’.

cache_size : float, optional

Specify the size of the kernel cache (in MB).

eps: (default: 0.001)

Tolerance of termination criteria.

C : float, optional (default=1.0)

Penalty parameter C of the error term.

nr_weight: (default: 0)

Number of elements present in the weight_label and weight.

weight_label:  (default: NULL)

Array of output variable values.

weight: (default: 1)

Weights corresponding to the elements present in the weight label array.

nu: (default: 0.5)

upper bound on the fraction of training errors / lower bound of the fraction of support vectors; acceptable range (0, 1]

p: (default: 0.1)

p value for significance testing.

shrinking : boolean, optional (default=True)

Whether to use the shrinking heuristic.

 

  • IE: Information extraction (IE) extracts structured information from unstructured and/or semi-structured machine-readable documents. It does NER (Name Entity Recognition), builds relationships (subject, object, predicate) and allows user to traverse knowledge graph to understand and extracts the hidden rules, conditions or information
  • IE Word Dictionary: IE can be applied for larger domain or specific ones. Therefore we need options to create a custom knowledge base for a particular domain. The word dictionary creation option allows us to create basic KB for a domain which allows us to train NER and IE models
  • IE Named Entity Recognition (NER): This is to extract named entity from a given text which are the basis for information extraction
  • Sentiment Analysis: Contextual mining of text which identifies and extracts subjective information in source material, and helps a business to understand the social sentiment of their brand or a product.
  • KMEANS:  This is an unsupervised learning model which is used to classify a given data set through a certain number of  clusters.
  • KMEANS Centroid: KMEANS uses various clusters and finds proximity to one or two clusters for classifications. The center of the clusters are known as centroid and therefore we could leverage centroids to understand how close or far a test data point is from given set of clusters
  • KMEANS Statistics: Various statistics are involved with KMEANS, such as mean, avg, centroid, etc. defined to understand the class of a given data point.
  1. Select the training speed of the model. This varies from Very Fast to Very Slow where Slow means that the data will be processed more accurately.
  2. You can choose an input stream using which you will train the model.
  3. Choose the type of attributes among string, number, hybrid (combination of string and number).
  4. Choose the file format in which you want the model to appear.
  5. Choose the training source where you need to specify whether you want to map the attributes with an existing stream or through an external source i.e., URL or File.
  6. Upload the training data. The format of the training data can be checked on the page by clicking on ‘here’. After uploading the data, click on ‘Start Training’ in order to begin creating the model.

Once successful, the model will be listed down on the right hand side of the page.

Yes No

4.7.BangDB Resource Storage (BRS) #

BangDB Resource Storage is meant for storing files especially training models in the BangDB server. It can be employed to store any type of object which provides data archives, storage for applications, backup and recovery. The basic storage units of BRS are objects which are organized into buckets.

Here are the steps you need to follow for creating a BangDB Resource Storage:

  1. Provide a bucket (similar to a folder) name.

2. Provide an access key that will give read only permissions to the users to view  the objects in the bucket.

3. Provide a secret key that will enable the users to access and edit the bucket as well as its objects.

4. Click on Create Bucket.

5. Once this is done, the bucket list will be enlisted on the right side of the page where you can upload the desired files in the bucket by using the Upload which appears when you click on the bucket name.

6. You can also check the list of uploading by clicking on Object List option.

7. To get an overview of the objects in the bucket, whether they have expired, the size of the bucket, and so forth click on the Overview option.

Yes No

4.8.Email Reports #

Timely analysis of the e-commerce data can be beneficial for the business teams to take quick actions and act upon the marketing strategies that would garner conversions. Mailing the business reports across teams is an ideal solution and would save a lot of time.

Email Reports feature available with the IQLECT’s ShopIQ App enables you to generate notifications related to the dashboard on a timely basis which can be shared with the members of your team. With this, you can keep an eye on specific aspects of your e-commerce business and generate useful insights.

Here are the steps you need to follow to create email reports:

  1. Provide a report name so that it becomes easier to recognise it.
  2. Choose a group with whom you want to share the dashboard.
  3. Select the Dashboard that you want to send via email reports.
  4. Select the time interval within which you want to be notified.
  5. You can also specify the time at which you want to receive the report. In case of weekly and monthly reports, you can choose the day on which you want to receive the reports.
  6. Give a small description about the report.
  7. Click Submit.

Once done the notification will appear on the right side of the app window. You can then disable, enable or delete it according to the requirement.

Yes No

4.9.Tag Manager #

Purpose of tag manager is to track events of webpage without changing the codebase.  This saves a lot of your time in generating data related to events on the website. To add a new tag, follow the given steps below:

  1. Provide the name of the tag.

  1. Provide an event name that you want to track for identification. Avoid giving a space in the name.

  1. Choose the type of tag which can be either an event/javascript code/third party code.

If Tag Type = ‘Event’   

  1. CSS Selector – If tag type is “Event”, this field will be enabled. You need to find the css selector of the particular element(path of the element) by inspecting the browser. CSS selector should include “.” or “#” depending on selector type.

Ex: To find out no.of clicks on “read more review” link use the following code:

<div id=’reviews’>

<div class=’review_item’> Review 1…<a href=’http://example.com’>read more review</a>

</div>

<div class=’review_item’> Review 2 .. <a href=’http://example.com’>read more review</a>

</div>

</div>

In this case, CSS selector is  “#reviews .review_item”

  1. Event type: Select the type of event you wanted to attach(click/hover)

If event type is hover, it will trigger the event when the user hovers on that element.

  1. Module name (Optional): This field identifies the module on which events are attached.

If TagType = “Javascript Code”

  1. Copy paste the javascript code in textarea, which you want to add in the store website. Code can be functions, variables etc.

If TagType = “Thirdparty Tags”

  • Copy past the third party scripts in textarea, which you want to add in the store website.

  1. Add relevant conditions by clicking +Add Conditions. Here you can restrict the event trigger based on your requirement. For ex: You can initiate the trigger event only in “chrome” or “chrome browser in mobile” etc.
Yes No

5.Analysis #

E-commerce businesses are presented with several challenges where they need to understand the customer behaviour so that they can provide them with better services and maintain visitor engagement, draw data insights that really matter, or determine the performance of a certain campaign – this is where the Analysis workspace can help.

The analysis feature provides you with the most powerful tools to determine the correlation between different streams, predict  the hidden data patterns that reveal meaningful customer insights, analyze data within a given period of time, and so forth.

Yes No

5.1.Correlate with streams #

Correlation can be used to show how different streams are related to each other. Using this feature, the users will be able to determine the dependency of two streams on each other and infer in-depth information from the e-commerce data for marketing effectiveness.

Follow these steps to correlate the streams:

  1. Select from the drop down list of the aggregated streams with group by attributes that you want to plot on the histogram.

2. Choose a stream that you want to display in the form of a table with its attributes.

3. Select the attributes that you want to plot for the histogram stream.

4. Select the granularity.

5. Select the time period for which you want to fetch data.

6. Click on Fetch Data.

Once the steps are completed, you will see a histogram and a table plotted for the chosen streams on the right side of the page.

Yes No

5.2.Stream Analysis #

The stream analysis feature enables you to examine high volumes of streaming data on your online store in real-time which can sometimes prove to be cumbersome to handle. Using this, you will be able to extract information from data streams and identify relationships between different streams. You can then use these information to trigger actions such as creating alerts and notifications.

The necessary requirement for this function is the presence of an aggregated attribute on which the analysis will be done. However, if no aggregation is available on any of the attributes, the system will prompt for an aggregation. Upon selecting the aggregation, a new stream will be created in the background.

Follow these steps for analysing a specific stream:

  1. Select the stream that you want to analyze.
  2. Select the time period for which you want the analysis report.
  3. Click on Fetch Data.
  4. In case there is no Aggregation (see section 5.2) on the selected stream, a pop-up window will open that will ask you to proceed with this step. Otherwise, you can choose an already created aggregated stream for analysis.
  5. You can then select an attribute that you want to aggregate with the stream and Click Create Aggregation. This will take you to the Aggregation feature of the Customize tab. You can follow the same steps for creating an aggregated stream as indicated in section 5.7.
  6. Once this is done, you will get to see a chart that indicates the analysis done on the aggregated stream along with a table that shows the data present in the specified data stream.
Yes No

5.3.Ad-hoc Query #

5.3.1 Ad-hoc analysis and its Use Cases

Ad-hoc analysis is a business intelligence process which can be used to answer specific questions related to your e-commerce business and helps in the identification of high-value customer segments using real-time data.

The Ad-hoc analysis feature available in the ShopIQ App would enable the e-commerce organizations to understand the sudden increase in customer churn and query the structured data to generate insights that are beneficial for the growth of the company. Using this, retailers can also determine factors such as price changes that might impact the sales, the reasons behind the fall in the number of customers, and the changes associated with the customer service metrics.

With this feature, you can analyse data within a given time frame using multiple charts and make faster business decisions that will be useful for your e-commerce business.

5.3.2 Applying Ad-hoc query               

Follow these steps to perform ad-hoc query on a stream:

  1. Choose data stream or a derived stream on which you want to run the query.
  2. Select     the ‘Group By’ parameter if required. Choose the type of chart that you want to be plot with the given data.    
  3. Choose the attributes that will be plotted on the chart.
  4. Apply filter on the data by entering an attribute, operator, and value.   
  5. Select the value for the chart axis. Provide stream names to the x-axis and y-axis for which you want to plot the graph.
  6. Choose time granularity & period for which you want to analyse the stream.

Once you are done with the above steps, click “Plot” to complete the ad-hoc query process.

Yes No

5.4.Predictive Analysis #

Predictive analysis combines the functionality of machine learning and data visualisation to help you analyze the impact of marketing activities, use predictive scoring to identify the probability of visitor engagement and understand the “what if” scenarios which can be used to predict business outcomes.

You can use the predictive analysis feature to target and predict the customer churn, their response on the website and whether they are likely to convert or not. This would help you to determine the best time and methods to create an impact on the targeted audiences.

Predictive analysis can be carried out in three stages which are as follows:

5.4.1 Training a model

Before applying predictive analysis, it is necessary to train your data and create a model using an external file or an existing stream which can be done by following the same steps as given in section 4.6.

5.4.2. Testing a model

In this stage, the user can test the model to predict the data that is either provided through an external file or through user-defined inputs for the chosen stream.

Follow these steps to test the model:

  1. Choose the model that you want to test and click on it. Doing so will show a window which contains the option of Test Prediction.
  2. Here you will be presented with two options to enter the attributes that you want to predict.
  3. One way is to assign values to the given attributes that you want to predict and click on Test. Doing so will generate a value of the predicted label.
  4. Another way is to choose a file format and drop a test file available in your system that you want to predict. Once done, click on Test. You can then download the result of this operation by clicking on Download Result.

5.4.3 Deploying a predictive analysis stream

Deploying is the final stage of the predictive analysis which involves the creation of a predictive analysis stream using the trained model and an input stream.

You can initiate predictive analytics by following these steps:

  1. Choose a main stream.
  2. Select the training model that you want to deploy.
  3. Click on Attribute Mapping. You will see a steam mapping page pop-up on the right hand side of the page. Here you will need to choose the stream attributes that you want to map with the attributes of the training model. When you are done with it, click on Submit.
  4. Provide a name for the predictive stream.
  5. Click Save.

A predictive stream will be created which will be visible in the Streams feature of Customize.

Yes No

5.5.Data Science (R) #

Data Science function enables you to analyze data within a given time frame and plot a chart of the attributes provided by the user using R programming language. This means that you can extract information for every single minute and analyse it to make business decisions.

The following functions can be used to plot a chart:

  • Density Plot:  Density plot is used for data exploration and analysis. It is similar to a histogram but height of the plot at a given x-value corresponds to the “density” of the data.
  • KMEANS: Plots KMeans cluster after analysis of the data.
  • Box plot: Compares the distribution of data across data sets by drawing boxplots for each of them.
  • Co-relation matrix: Used to investigate the dependence between multiple variables at the same time.
  • Histogram: Represents the frequencies of data values of a variable in continuous ranges.
  • Matrix of Scatter plots: This is a useful way to visualize the relationship between two variables.
  • Regression Diagnostics: Determining whether a regression model fit to the data adequately.

5.5.1 Generating summarised report of a stream using R functions

You can perform R analysis using the following steps:

  1. Provide a name for the report.
  2. Select the type of analytical function to perform.
  3. Depending on the function there may be another field to choose arguments or algorithms
  4. Select the input stream.
  5. Map the attributes on X-axis, Y-axis and Group-By.
  6. Select the time period for analysis.
  7. Click Save to complete the query creation
  8. Click the button under column “Run Report” against the report name to run the report,
  9. Upon successful completion, the report can be viewed by clicking on the “eye” icon on the right end of the report name.
Yes No

5.6.Complex Event Processing (CEP) #

Complex event processing is a process that combines data from multiple sources to draw infer patterns or events that suggest more complicated circumstances. The goal of this process is to identify meaningful events such as the ones related to sales leads, orders or customer service and take actions on them as quickly as possible.

The complex event processing feature is a time bound and a condition-based operation on events which allows the user to create complex streams. This feature can be used to correlate different attributes between streams.

5.6.1. Initiating operations in CEP

There are two main operations for complex event processing that are provided by the IQLECT’s ShopIQ app which are as follows:

  1. Filter streams: It filters the streams according to a specific condition.   
  2. Combine streams: It combines two different streams to form a completely new stream which can be used for in-depth analysis on the business metrics.       

Steps to use of the filter streams:

  • Select a data stream or derived/analytics stream to be filtered.    
  • Select    the condition and attribute to be filtered.    
  • Choose the attributes for the new stream. You can also add more attributes by clicking on ‘+Add attribute(s)’.    
  • Provide a stream name for the output stream.

Steps to use the combined streams:

  • Select  the two streams to be combined. The attributes from the second stream should be a subset of the first stream if there is a looping condition.    
  • Select the output attributes > Click and select the attributes from stream 1 and stream 2. You can add new attributes by clicking ‘+Add attribute(s)’.
  • Provide a joining condition as stream 1 and stream 2 will be combined when this condition meets. You can add more conditions if required.    
  • Create a loop for the condition that will create a boundary parameter for checking the condition. Specify the number of times the condition must be met in the given time frame.    
  • Define the looping condition using the “Add Condition” link in the “Where” section.
  • Click “Till” checkbox to provide the condition to break the loop.    
  • At last, give a stream name for the output stream.
Yes No

5.7.Aggregation #

By collecting e-commerce data for a specific purpose, you can apply calculations across different business metrics such as abandoned carts, orders placed from a specific city and so forth,  and then use the resulting high-level summary information to present overall statistics of your business. This will help you to draw new insights and relationships in data which you can further use to boost your business performance.

The Aggregation feature can serve this purpose effectively and allows you to perform aggregation operations such as average, max, min, count and cardinality on a given data stream which process the data records and generate the computed results as events for the new output stream. You can also groupby on different attributes.  Apart from that, you can also apply the top-K query which will return top ‘k’ (user-specified) values of the chosen attribute.

Operation

Description

Average

Calculates the running average of the selected attribute.

Count

Counts the rows in a specified stream.

MIN

Gets the minimum value of the selected attribute over time.

SUM

Calculates the sum of values over time.

MAX

Gets the maximum value of the selected attribute over time.

Cardinality

Calculates the number of unique values of the selected attribute.

5.7.1 Aggregating a stream       

To aggregate a stream, follow the steps given below:

Step 1

Select an input stream. This is the stream whose (one or more) attributes will be aggregated. Upon selecting the input stream a section appears to aggregate its attributes.

Step 2 (Aggregation)

  • Select the type of aggregation (Average, Cardinality, Count, Maximum, Minimum, Sum) to be performed.
  • Select an attribute as an input.
  • Provide a name to the output attribute.
  • If you want to select indexing, accumulation of data or calculate percentage values then check the respective box.
  • Add another attribute (if required) by clicking ‘+Add Another Attribute.’

(In case of Top K aggregation)

  • Top K aggregation lists the ‘Top K’ attributes in a stream. This can be performed only if the input stream contains at least one numerical and one string attribute.
  • Select the attribute as an input.
  • Select the value of K (e.g. Top 10 feature will have a K value of 10)
  • Select the order (ascending or descending)

Step 3 (Group or Unique)

  • Select an attribute to group the aggregated values.

(In case of Top K aggregation)

  • Select an attribute whose values should be unique.

Step 4

  • Provide a name to the output stream.
  • Upon submitting the form the aggregated stream is created.

Once done, the list of aggregated streams will appear. You can then analyse, visualise, drill, or take actions on the stream as indicated by the launch icons present on the right side of the stream name.

Yes No

5.8.Long Term Analysis #

Long term analysis is a practice which includes the collection of historical information and help businesses to recognize patterns or trends. Long-term analysis is used to create a static stream and analyse that data for a longer period of data.

Long term analysis allows a user to do the following things:

  • Aggregation of data over longer period
  • Aggregation between multiple streams
  • Generate new stream by using attributes from the input stream
  • To identify patterns in input data
  • To refer one input stream data by other stream

Here are the steps you can follow for long term analysis:

  1. Create a new stream by providing a name to it.
  2. Click on +Add Attribute. A window will appear where you need to select a stream which can be used as an output stream.
  3. The list of attributes that are associated with the selected stream will appear at the bottom of the window which are color-coded according to their data type.
  4. Click Next.
  5. You will now need to add the attributes for the selected output stream. Provide the attribute name, attribute type, and whether or not you want them to be indexed. Add additional attributes if required > Click Next.
  6. Choose the input stream and define an operation on its attributes. You can either choose the input stream attributes or the output stream attributes on which you want to apply the operation. Click Close.
  7. Click Done.

Once you have completed the steps, you will be directed to the Streams Page in the Customize feature where you can view the stream on which long-term analysis will be done.

Yes No

6.App Settings #

The App Settings allow you to transfer data from your e-commerce website to the BangDb Server which can be later retrieved as per the business requirement.

Here are the steps that you need to follow for initiating the transfer process:

  1. Choose a stream whose data you want to send to the BangDb server, the information about which will be indicated in the sending instructions. The instructions are available in Python, Java, Javascript, Ruby, and C.
  2. Click on Download Client so that the script gets downloaded on your system in the form of a zip file. You can also refer to the Instructions provided on the extreme right corner to get a clear idea on following the settings procedure.
  3. You can then Copy the chosen code instructions in the command prompt and run the code to initiate the process.
  4. Once the query is executed, you will get a message (need to specify it) for successful implementation of the query for the transfer of data from your e-commerce website to the BangDb server.
Yes No

7.Reference Data #

E-commerce companies need to keep a record of data related to their premium customers, orders, or products along with other metrics that they receive on a daily basis so that they can utilise the collected information for developing marketing strategies and boosting business performance.

Every data point collected over the course of time can be beneficial for the growth of the company and for this the reference data feature can serve the required purpose.

In case you want to use historical data to correlate with the streaming data then you can use the Reference data feature and transfer files to and from BangDB (platform developed by IQLECT) to local file systems or Hadoop file systems.

Here are the steps that you need to follow to use this feature:

  1. Select a data source and destination from the drop down list where you want to transfer the files. Click Next.
  2. Copy the command that is generated and run the same on your system. You just need to perform this step during the time of installation.
  3. Provide the path of the file that you want to upload or download. Select the relevant file type, data type, key type, and so forth for this file. Click on Generate Command.
  4. A command will be generated which you can Copy on your machine for uploading or downloading the data. Clicking on Edit will take you back to Step 3.
Yes No

8.Help and Support #

Account and Notification Settings

How can I change my password?

To change your current password, follow these steps:

Click present on the top right corner of the home page and choose Account.

  1. Under Change Password mention the Current Password > New Password that you want to change > Confirm the new password > Change Password.

What is the Generate New Key option in Account used for?

When you click on the Generate New Key button, a key is generated which can be used for accessing the data from the BangDB server. This key can be integrated in the code that is generated in the App Settings feature for further use.

How do I log out of the ShopIQ App?

You can log out of the ShopIQ app by going to your profile.

  1. Click present on the top right corner of the home page and select Log Out.

How do I add new users on ShopIQ App?

The Users page allows you to add users who can be notified when certain events happen. These users can then be put in ‘Groups’ where they can be provided with special set of privileges.

Here are the steps to add new users:

  • Click on the top right corner of the home page and select Users.

  1. Choose +New User.

2. Fill in the basic details such as Name, Email, Phone, and Description.

3. Click Save.

The saved details will then be visible on the page.

How do I add new group on ShopIQ App?

You can create a group on ShopIQ App to streamline the notifications and provide similar privileges to the people in the group. Follow these steps to form a group:

  1. Click on the top right corner of the home page and select Groups

2. Choose +New Group.

3. Fill in details such as Group Name, Description, the Users with whom you want to form the group.

4. Click Save.

Once created, the following details about groups will be shown on the page:

  • Group name: Name of the group
  • User count: Number of users in the group
  • Edit: Option to edit group details such as name and description

How do I set notifications on my account?

The notifications that you create through the Actions feature (see section 4.2) will appear at icon present on the top right corner of the home page.

How can I use the Support feature?

You can use the Support feature for queries related to the app.

  1. Click on Support option present on the top right corner of the home page.

2. You will see a pop-up window where you need to add a relevant subject, description, and attach the files or screenshots of the issues that you are facing in the app using the Browse option.

3. Click on Done.

Your request will be directed to tech@iqlect.com where our technical support team will guide you through the problem.

Yes No