Everyone wants to know how the upper funnel affects the bottom line, how actions that started at one touch point manifest at another. Each tool has its own analytics, residing outside of the main analytics. Google AdWords and Facebook have their analytics, Mailchimp has its own reports, as well as payment tools, CRM, customer satisfaction and all the others, making it impossible to see a consolidated view.
What if you can get information like, ROI from a recent Google Ads or Facebook campaign, see the latest buying trends of your customers, engage inactive users, or even compare offline campaign data with user behavior analytics on your app? Having a smart way to blend your data sources into a single view is critical.
Enrich user events with external data files
By enabling the Google Cloud integration, you can integrate the data from any type of file on the Google bucket with your advanced behavioral data. Media and e-Commerce companies find this extremely useful for cross referencing enrichment data from Google bucket such as product prices in conjunction with behavioral data from their website
A media company uploads audio and video metadata into Google Bucket that would be too cumbersome to send along with the events. So, when a user buys a track or video on the website, the event is sent with the product ID and then matched with the metadata taken from Google Bucket. This way the marketing team can get insights on the most popular items to create data driven promotions, or target specific user profiles.
Spice behavioral data with offline data
Blend behavioral data with external reports that are sent as email attachments. Such reoccurring emails may contain CRM activity data, support statistics, customer feedback or even offline campaign rating data. To blend this into your behavioral data, enable the eMail integration, configure it to search the defined inbox for a specific syntax in the subject line, on a set schedule. It will fetch the data from the attached report and pour it to the main database.
A nice use case would be of one media company that runs TV ads promoting their online products. All offline advertisement data, including the number of times the ad was run, the number of people it reached and on what time of day, is sent daily as reports attached to an email. With the email integration, such valuable data is combined with the behavioral data of their online assets and becomes useful when with a multi-channel attribution analysis, to find the relation between the time at which a new user saw the TV ad, and the time that user visited the website or performed an action event.
Others use this email integration to take in customer support related data, such as feedback or ratings to be joined with user behaviors from that day. This helps to get immediate view of UX issues, faults or malfunctions.
Measure campaigns ROI and user Lifetime Value
Blend Google AdWords or Facebook Ads campaign data with behavioral data. Determine you users’ lifetime value or calculate a campaign’s ROI by crossing Ads impressions or click-through rates with event based behavioral data.
With the blended data you may write a query that determines a user’s lifetime value by taking his cost of acquisition from the Facebook Ads or Adwords campaign and compare it against the sum that user has spent during his lifetime on the application.
To close the loop, you can then target your Facebook or Google campaigns, based on that analysis, to reach the ideal group of users with the higher lifetime value.
email campaigns data plus event based behavioral data
Compare the results of a particular email campaign with event based behavioral data collected from your website or application. You can correlate the number of email opens or click-through rate from an email campaign, with the number of downloads, signups or any other conversion.
Back in MailChimp or another email campaign tool, you can utilize the user report, to send out a follow up email to those contacts that have dropped off somewhere on your buyer’s journey.
Use behavioral data to boost customer retention
Integrating with Stripe payments data is extremely valuable when combined with behavioral data. Payment properties of a user like payment method, number of installments, or other factors become useful when you think a customer might stop or change their subscription plan. With this integration, one of our customers learned that a user will cancel their subscription plan after five weeks of inactivity on their site. Now, they are retaining more users because they are able to target at-risk customers with extra features and discounts before they cancel.
Every multi channel online business with multiple data points can realize the advantages of analytics based on wide, unified data set.
The next generation of BI is already here! CoolaData is a complete big data behavioral analytics solution, including seamless integration with multitude of external and internal data sources, as the base for advanced behavioral analytics, covering the comprehensive business insights from a richer analytical framework.