User manual for ShopIQ 1.0

IQLECT's ShopIQ 1.0 App Manual

1.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. IQLECT’s Shopify 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 270+ KPI, predictive models, and enhanced visualization from 30+ 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 IQLECT’s Shopify app an ideal choice to analyse your online store:

Interactive Landing Page

The IQLECT’s Shopify 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.


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 IQLECT’s Shopify app, you can process such information easily and make instant business decisions to boost conversions.

Report notifications

Users of IQLECT’s Shopify 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 IQLECT’s app on your shopify platform 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.

Ad-hoc analysis

With functionalities such as ad-hoc analysis you can extract information within a time range and make business decisions that would be profitable. The data generated would be useful in determining the critical points in the business process at any point in time.

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. IQLECT’s Shopify 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.

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1.1.Getting Started #

How does the app works?

Install the App

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

Installing ShopIQ


Once the app is successfully set up, the data will start streaming instantly. You can access the functionalities 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.

visualising the ShopIQ


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.

Analysing data with ShopIQ


You can customize the dashboard and add advanced capabilities to deliver user engagement and drive high-value outcomes. By training models, creating charts, and customising 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.

How to customize ShopIQ app
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1.2.Video Demonstration #

Take a look at the general overview of IQLECT’s Shopify app along with a brief demonstration of the in-app features here:

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1.3.Installing the app #

Shopify account users can install the app by following the given steps:

1. Sign in to your Shopify account > Click Apps in the left-hand side menu of your admin page.

2. Tap the Visit Shopify App Store button > Enter the ShopIQ in the search bar.

3. Once the app detail page opens, click on Add app.

4. You will be directed to your admin page where you can click on Install Unlisted app button.

5. You can also opt for the free trial, the option for which will appear on the right side of the window

6. You will now be taken to the login page to Create a new IQLECT account. Provide your email id with which you have registered on Shopify along with the password.

7. Click on Submit to finish the installation process.

What to do next?

• When the installation is complete, you will be directed to the homepage of the app where you can access the dashboard by clicking on the My apps tab.

Choose the Apps option present in your admin page.

Note: IQLECT’s Shopify App ‘ShopIQ’ is available for a 15-day free trial.

There are 3 versions of ShopIQ available for Shopify users.

Free version – Access to all real-time insights

Basic – $19/month – Advanced forecasting features with real-time Analytics

Pro – $399/month – Unlock full capabilities of Real-time predictive analytics platform

For more info: Visit ShopIQ for Shopify

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1.4.Uninstalling the app #

To uninstall the app, follow the procedure given below:

1. Choose the Apps option present in your admin page.

2. In the Installed apps list, click on the delete icon present on the right hand corner of the IQLECT’s app.

3. When the Uninstall window pops-up, simply click Uninstall.


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1.5.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 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.
ShopIQ Landing Page
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2.Dashboards #

Dashboards are a collection of widgets that give you an 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 dashboards. 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.   

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2.1.Dashboard 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 website.

Dashboard overview

Chart Description
Session Count Total number of unique sessions.
Visitor Count Number of unique visitors who accessed the website.
Total Sales Total sales made in a given period of time.
Page Views Number of pageviews at a given period of time.
Overall Bounce Rate Overall percentage of visitors on the website who navigated away after viewing only one page.
Overall Conversion Rate Number of conversions upon the number of visitors.
Page Views Per Session Number of page views in a particular session.
Average Session Duration Average time at which a session lasts.
Site Profiling Contains information about the website such as its connection time, load time, lookup time, response time.
Average Load Time Average time taken by the page to load.
New Visitors Number of new visitors on the website.
Returning Visitors Number of returning visitors on the website.
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2.2.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 total sales, order values from a specific country 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.

Order analysis

Chart Description
Total Sales Total sales made at a given period of time.
Orders Count Total orders placed at a given period of time.
Average Quantity Per Order Average quantity of items in an order at a given period of time.
Average Order Value Average order amount.
Average Data for Orders Contains basic information orders such as average discount, shipping charges, tax, etc.
Average Order Values by Country Average order amount sorted by country.
Orders Placed VS Cancelled Amount Proportion of orders placed and cancelled amount.
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2.2.1.Order Analysis by Details #

Using this dashboard, you can determine the details of the orders that were placed recently. You will also get to know about the quantity of sold products, total price of the items along with other order related information.

Order analysis by details

Chart Description
Recent Order Details Details of the orders that were placed recently. Number of entries in the table can be chosen as per requirement.
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2.2.2.Cart Analysis #

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

Cart analysis


Charts Description
Abandoned Carts   Information about the products that were added by the customers in the cart but left without checking out.
Cart Value   Item count along with total discount and the item price for the past week, day, or even seconds.  
Number of items in Cart Number of items in the cart.
Order Progress Status   Includes a table that shows status of a particular order. The values that are indicated here include cart token, user id, product names, and product id.
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2.2.3.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.

Order analysis by checkout

Chart Description
Orders Funnel Shows the number of items at different stages of checkout along with total number of items that were placed or cancelled.
Checkouts Shows the number of checkouts made.
Products in Checkout Table that shows the products that are in the checkout stage.
Checkouts by Price Range Price of products in the checkout
Checkouts Value Price of items in the checkout stage which is calculated for every session.
Products in Checkout Tree map that shows the category of products in the checkout stage which is then further bifurcated into the product name.
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2.2.4.Order by Discount & Payment #

This dashboard can help you determine the order count, order amount, and total discount on the orders depending on the discount code. You would then be able to analyse the status of orders according to the discount applicable on them and the payment methods used by the visitors the most.

Order by discount

Chart Description
Total discount by discount code Total discount on order according to the discount code.
Order Amount by payment type Order value according to the payment type such as credit card or cash on delivery.
Orders Amount by discount code Total amount of orders using discount code.
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2.2.5.Cancelled Order Analysis #

This dashboard can help you determine the intricate details related to the cancelled orders such as the product details, and the time at which the orders were cancelled.

Cancelled order analysis

Chart Description
Cancelled Orders Number of cancelled orders along with their total amount.
Cancelled Orders Details Details of the order that were cancelled.
Cancelled Products Details Details of the products that were cancelled.
Cancelled Order Details by Time Time at which the customers cancelled an order.
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2.3.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


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2.3.1.Visitors by geo #

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

visitors by geo


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


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2.3.2.Visitors by browser #

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

visitors by browser

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
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2.3.3.Visitors by device #

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

visitors by device


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.
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2.3.4.Visitors by user history #

This view is all about the overall user history and information about purchases made.

Visitors by user history

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2.3.5.Visitors by campaign #

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

Visitors by campaign

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
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2.3.6.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.

visitors by os and nw


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.
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2.4.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.

Product analysis

Chart Description
Products Viewed Products that were viewed by customers at a given period of time,
Popular Products by Sales Popular products based on the sales made.
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2.5.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
Customers Online Number of unique customers who are online.
Total Amount Spent Total amount spent by the customers.
Total Orders Total number of orders placed by a customer.
Average Order Value Average value of the order.
Customers by Product Count   The number of products purchased by a customer.
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2.5.1.Customer LTV #

This dashboard indicates the lifetime value of registered customers once there is sufficient data available to train the prediction model.



Chart Description
Customer’s Lifetime Value Lifetime value of a particular customer
Lifetime Value by City Lifetime value of a particular customer based on city.
Lifetime Value by Country Lifetime value of a particular customer based on country.
Lifetime Value by UTM Source Lifetime value of a particular customer based on UTM source.
Lifetime Value by Referrer Site Lifetime value of a particular customer based on the referrer site.


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2.6.Scoring Analysis #

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

Scoring analysis

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

  1. Go to the visitor dashboard and click on the 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 Score   Sessions present in a given score.
Score Details Details of a customer based on the chosen session.
Sessions by Average Score   Sessions with average score.
Sessions by Discounts Shown   Sessions that have discounts.
Purchased Sessions by Discounts Code   The number of people who purchased products using the discount code.
Score Information   Information related to the generated customer score.

User Analysis

Scoring analysis1

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2.7.Conversion Analysis #

Conversion Analysis allows you to define visitor conversion events for analyzing the behaviors of the customers who have converted to those who did not convert.

Conversion analysis
Chart Description
Conversion Rate Last Minute Visitor conversion rate in last minute.
Conversion Rate Last 30 Minute Visitor conversion rate in last 30 minutes.
Conversion Rate Last Hour Visitor conversion rate in last hour.
Conversion Rate Last Day Visitor conversion rate in last day.
Conversion Rate Last Week Visitor conversion rate in last week.
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2.8.Page Analysis #

The Page Analysis dashboard shows you the number of views for each tracked page on your website and helps in determining the pages which are being visited the most. This dashboard can be used to:

• Identify the web pages that are being visited less, so that you can highlight them more prominently.

 • Measure page views to promotional, sign up, or order pages for marketing effectiveness

 • Monitor the traffic on all pages through readable charts/widgets.

 • Determine the pages or products in which your customers are interested.

Page analysis

Chart Description
Page Views   Displays the number of views on your website depending on the time for which you want to gather insights, browser type, and device.
Average Views Average number of views on a particular page.
Exit Rate Across Pages Exit Rate is the percentage of visits that were the last in the session.
Page Views by Browser Total number of page views made through a browser
Page Views by Device Type Total number of page views made through a device.
Page History Displays the total number of views, bounce rate, overall exit rate,   
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2.9.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.

Campaign analysis

Chart Description
Order by UTM Source Orders that were made customers who reached the website through a referring site.
Visitor by Campaign Visitors who reached the website through a particular campaign.
Campaign Details Details of the campaign.
Sales by Campaign Sales made through a campaign.
Total Sales through Campaign Total Sales made through a campaign
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2.10.Events #

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


Chart Description
Event Count Number of events generated in a day such as page scroll, add to cart, etc.
Events Count by Device Type Number of events generated from a specific device such as mobile or desktop at a given time period.
Events Count Per Page Number of events generated on a page at a given time period.
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2.11.Marketing ROI #

 Return on Investment (ROI) is a performance measure used to evaluate the efficiency of an investment or compare the efficiency of a number of different investments. ROI tries to directly measure the amount of return on a particular investment, relative to the investment’s cost.

Marketing ROI


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2.11.1.Facebook Ad analysis #

This view of the dashboard is for analyzing Facebook ads which has Utm campaign information, total clicks, impressions, CPC, CPM, CTR and demographics analysis.

FB ad analysis

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2.12.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.

Traffic flow

Chart Description
Traffic flow Shows the flow of customer traffic on the website at a given instance of time.
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2.13.Mobile analysis #

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:

mobile analysis


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
Bounce Rate Bounce rate of the website
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.
Mobile Views Number of views on the website through mobile.
Stats by OS Shows the details related to the visitors, page views, sessions, and average load time based on the operating system.



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2.14.Referrer analysis #

Referrer analysis dashboard showcases the numbers of visitors, orders, and sales made through a referring site. This would help in determining the traffic you are receiving from a specific referral site so that you can devise strategies to use such sites effectively.

Referrer analysis

Chart  Description
Sessions through referrer Number of sessions based on a referring site.
Visitors through referrer Number of visitors who reached the website through a referring site.
Orders through referrer Number of orders placed through a referring site.
Total sales through referrer Total Sales made through a referring site.
Visitors by referrer Number of Visitors  distributed according to the referring site they used to reach the website.
Sales by referrer Sales made through different referring sites. 
Sales by referrer (Table) Contains details about the referring site, unique visitors, and total sales made.
Orders by referrer Orders placed through different referring sites. 
Referrer Details  Contains details related to the referrer site, unique sessions, and count.
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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 the 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.

notification template
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3.1.Adding Notification Templates #

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.

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4.Customize #

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

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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 the IQLECT’s Shopify App, the destination source is Ampere 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: (will be included when added on the app)
    • 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. 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
Takes the user to the aggregation wizard where they can modify the stream as per the requirements.

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.

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.

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4.2.Actions #

Notifying the team members regarding about 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 is value to be configured.

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

5. Occurrence: Defines the frequency of occurrence upon which the action is triggered.

6. 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.

7. 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 Shopify 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: Itillustrates 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. You can add up to five queries for the analysis.
  • Comparative Analysis: Used to plot data trend between two time periods. You can add maximum one stream and two attributes.
  • Trend Analysis: This is similar to normal analysis but it is plotted on archived data.
  • Cumulative Analysis: Used to plot chart with cumulative data within given intervals.
  • Static Analysis: Can be plotted by taking any parameter (other than time) on x-axis.

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

3. 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.

4. Upon selecting the stream, the attribute codes are displayed on the pop-up window.

5. 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.

6. 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.

7. 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.

8. Add more query if necessary or plot the chart to see the preview.

9. In order to save the chart, click on +Save Chart.

10. A window will appear on the right hand side where you can provide details for the chart including the title, subtitle, description.

11. 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 the from the drop down list and click on 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 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 extracts 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 a 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.

3. 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.

4. You can choose an input stream using which you will train the model.

5. Choose the type of attributes among string, number, hybrid (combination of string and number).

6. Choose the file format in which you want the model to appear.

7. 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.

8. 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.

9. 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 Bang DB 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 option which appears when you click on the bucket name. 
  6. You can also check the list of uploaded files 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 on a lot of time.

Email Reports feature available with the IQLECT’s Shopify 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. Give a small description about the report. 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 receive the reports.

6. 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.

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

3. 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=’’>read more review</a>


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



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

a. 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.

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

If TagType = “Javascript Code”

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

4.10.Email to Customers #

Emailing is an inexpensive way to advertise your company and its products and/or services compared to many other types of marketing. “Email to customers” can be used even during campaigns. One of the most obvious advantages of email marketing is its lower cost compared to mainstream marketing channels.

1. Select a mail template by creating an account on Sendgrid ( ) You now need to copy the sendgrid API key that is generated and paste it in “Sendgrid Settings” which is present in “App settings”.

2. Select the data you want to send from the drop down list.

3. Map all the template variables correctly. If you want you can also enter a custom value by select the last option that is present at the end of the drop down list.

4. In the “Additional parameters” section, you can select whether you want to send the mail to custom users (single user or multiple users, if multiple then separate the email-id’s by commas) or to all the users.
5. Enter the name and email id of the sender.

6. Select the Unsubscriber list from the drop down.
7. After entering all the details you need to click on ”Send email” option which is present at the bottom of the window.
8. If you want you can save the template by clicking on the “Save for future” option.

Once done, all the saved templates will be visible on the right side pane.

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  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 a 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 5.7) 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 5.7.1.

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 analysis #

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 Shopify 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.

Yes No

5.3.1.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 analytics #

Predictive analysis combines the functionalities 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:
– Training
– Testing
– Deploying

Yes No

5.4.1.Training #

Before applying predictive analysis, it is necessary to train your data and create a model which can be done by following the same steps as given in section 4.6: Training a model

Yes No

5.4.2.Testing #

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.

Yes No

5.4.3.Deploying #

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.
Yes No

5.5.1.Reports using R #

Creating an R report

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 #

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 bounded and a condition-based operation on events which allows the users to create complex streams. This feature can be used to correlate different attributes between streams.

Yes No

5.6.1.Setting up CEP #

There are two main operations for complex event processing that are provided by the IQLECT’s Shopify 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:

1. 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.

2. 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)’.

3. Provide a joining condition as stream 1 and stream 2 will be combined when this condition meets. You can add more conditions if required.     

4. 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.     

5. Define the looping condition using the “Add Condition” link in the “Where” section.

6. Click “Till” checkbox to provide the condition to break the loop.     

7. 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 integer) values of the chosen attribute.

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.

Yes No

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.

Aggregation Streams
Top K Streams
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 pattern or trends. Long-term analysis is used to create a static stream and analyse that data for 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 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 the 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 follows to use this feature:

1. Select a source and destination from the drop down list where you to 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. 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.Known Issues #

IQLECT’s Shopify app has the following known issues:

  • If a parent stream is linked to multiple dependent streams, it always plots the stream which is the depending on it.
  • Name of dependent stream in “Drill through Stream” is not visible. The same behaviour is noticed for “Drill Down” stream when there is only one dependent/derived stream of the parent.
  • Labels and their description overlap when charts are created from stream analysis. This issue is visible when the mouse/cursor is hovered over the chart.
  • Charts plotted during “Stream Analysis” appear cluttered when you hover the mouse over them or when the data points are more.
Yes No

9.Help and Support #

Here are few FAQs related to Shopify app:

How can I change my password?

To change your current password, follow these steps:

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

2. 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 Shopify App?

You can log out of the Shopify 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 Shopify 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:

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

2. Choose +New User > 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 Shopify App?

You can create a group on IQLECT’s Shopify 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 Group.

2. Choose +New Group > Fill in details such as Group Name, Description, the Users with whom you want to form the group.

3. 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 where our technical support team will guide you through the problem.

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