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Build the right
customer segments

Gain the ability to segment data and build intelligence for seamless data insights that make your
job as a business owner easy.

When you choose clean and structured data powered with ML &
AI, you reduce the time it takes your data experts to build intelligence on data from disparate

Get a panoramic view of your customer's journey

In a world where marketers spend billions in wooing their customers, how will you stand

Get to know your customers and their entire journey with an end-to-end
solution. Predict your customer's next move with pre-built analytical models which are
customizable and simple to use.

Get the bugs and
loopholes in real-time

A retailer's nightmare? Abandoned carts

Why do your customers abandon carts online or
offline? What is it that makes their journey difficult? Is there something your competitor has been
doing that you oversaw?

What is a Knowledge Graph
Enabled Customer 360 Solution?

This is an era where companies are looking to build superlative customer experiences to facilitate
long-term brand loyalty. Having a robust data management platform like DataBlaze can provide an
integrated view of the customer journey and build this superior experience.

Learn More

Algorithmic Attribution for
channel contribution
RFM Model for customer recency
Recommendation Model for offers and/or
Probabilistic Clustering for
Customer Segmentation


Customer 360 provides a contextual view and understanding of your
customer's journey from multiple views. Our pre-built analytical models provide deeper customer
insights and allow better business decisions.

Algorithmic Attribution
for channel contribution

Use data and automation to effectively determine which ads, content, and
engagements received more credit for the interaction.

The algorithmic attribution model ensures credit is not being unfairly weighted towards specific
pieces of content. It helps examine their journey and attempts to assign credit, based on data, to
different pieces of content in the funnel.

  • This method helps you pin down every channel's proficiency over a time span and identify
    underperforming ones.
  • It helps you evaluate the performance of each click and interaction


Top brands make crucial decisions based on the analytical recommendation model.
So we have pre-built it for you!

Let DataBlaze take care of the modelling while you make the
right decisions. Voila! You have loyal customers.

  • A recommendation engine helps bring traffic to your site
  • The volume of data required to create a personal shopping experience for each customer is too
    cumbersome to be managed manually. Automation eases the process of structuring the data and
    creating varied recommendations.
  • Providing reports to clients can generate insights for slow-moving products to create a drive in
    marketing and sales for those products.

RFM Model for
customer recency

Understand and segment shoppers down to the store level to run more effective
local advertising and product features.

Change the attributes of your CLTV per selling season or sale cycle to understand the value of
seasonal shoppers.

The trusted Recency, Frequency and Monetary model is a marketer's

  • Increased customer retention.
  • Improved response rate.
  • Elevated conversion rate
  • Inflation in revenue.

Probabilistic Clustering
for Customer Segmentation

Retaining a customer's interest for a long while is challenging.
Probabilistic customer segmentation is a favored method to predict customer behaviour and tailor
your marketing campaigns based on those predictions. The only trouble? The analytical model takes
months to build—DataBlaze automates that task for you.

  • Marketing efficiency: Identification of your target audience quick and easily. Campaigns can be
    launched for the most relevant people using the most relevant channel.
  • Enrich your records: Easily find and analyze the data for segmented customers using interactive
    charts and graphs without a need to create complex algorithms.

Hear from our Experts

Make crucial decisions
with all the information
at hand
Schedule a Demo