Capture, aggregate, analyse & report, and predict customer needs and wants


Customers buy when they have a need, not because organizations sell.

But how do you anticipate these needs?

Till 20 years ago, needs were analyzed for large segments of customers.

Till a few years ago, needs were analyzed for segments of 1.

Now, with modern AI systems, the needs of a particular customer can be analyzed, changing from moment to moment.

How do you do that?

The Data to Insight journey has multiple stages:





Analyze & Report





Customers leave clues all
over the place

when they

use your
products and

use your
products and

email you

walk into your

update their
Facebook pages

Some of these clues are already captured in databases in different transaction systems. Some of these customer actions are not captured. Customer behaviour on portals and mobile apps for example. The first step is to identify and capture all the sources of data that represents customer behavior.

Xerago identifies key data gaps and also implements tools to capture missing areas, using tools such as Adobe Analytics, Ensighten Tag Management Systems, and other capture mechanisms.


It is not enough to capture data in different systems and sources. Without stitching these heterogeneous data sources together, you can only get a fragmented picture.


your web analytics platform tells you that a particular IP address spent time on a product page of your website.

When you marry that information with your transaction systems, you figure out the IP address belongs to an existing customer.

Targeting that customer with the relevant offer now becomes trivial.

You can aggregate data in a
number of ways. Usually, we use


tools to aggregate all the data into a Data Mart, or a Data Warehouse of some kind. Once aggregated, this Data Mart becomes your system of record.

Xerago implements and maintains both closed source and open source

“Extract-Transform-Load” solutions to help organizations aggregate and organize data.


The next step is to analyze performance.

Screenshot from 2018-11-26 15-57-43

How did your marketing campaigns perform across channels?

Screenshot from 2018-11-26 15-57-43

Which region showed the maximum growth over the past period?

Screenshot from 2018-11-26 15-57-43

Did seasonality play a role in driving sales?

Screenshot from 2018-11-26 15-57-43

Which offers were the most effective?

All these queries get answered in the form of marketing and business dashboards and reports that give a clear visual of performance.

Xerago uses Digital Analytics, Business Intelligence and Visual reporting tools to derive metrics, design reports and dashboards, drill-down and analyse reasons for outcomes.


Finally, to help

understand causality

group customers into homogeneous groups of segments

predict behaviors and outcomes

Likelihood of conversion (response rate prediction, for upsell or cross-sell)

Lifetime Value

Propensity to engage and stay loyal to your brand

Categorization (market basket analysis)

Likelihood of attrition (churn modeling)

Share of Wallet

Frequency of purchase

Xerago can help with any stage of your data journey, whether your organization has just taken its first tentative steps in this journey, or whether your Data Scientists have already deployed a bunch of models that you need maintained and improved to ensure that the models stay robust.

Xerago's Data, Digital and Marketing Analytics practice tracks metrics, delivers dashboards and reports and predicts behaviours and outcomes using a multitude of Business Intelligence and Analytics tools, statistical models and machine learning / AI systems.


About Xerago

Xerago invented the concept of Customer Value Maximization to help organizations leverage their customer portfolio in the modern world driven by digital interactions. Xerago works with some of the leading organizations of the world to maximize customer value.


At Xerago, we are always on the look out for bright, exceptional talent. To see what positions we are currently hiring for, please visit Xerago’s Careers page.

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