ACCURITY DATA VIBES: Data Contracts: The Cornerstone of Data Mesh and Governance


Market Basket Analysis for a Financial Services Broker is part of the major Czech investments and services broker group DRFG. We provided with market basket analysis to help them understand the relationships among its products and services so that it was possible to significantly increase sales through their e-shop, online campaigns, and CRM, plus confirm that their sales strategy was correct.


Use market basket analysis to increase sales and confirm the current sales strategy offers investments, insurance services, and mortgages. They wanted to use market basket analysis to:

  • Obtain cross-sell / upsell possibilities for their current clients.

  • Identify any areas of missing data.

  • Prepare data for further use in CRM.

  • Confirm the current sales strategy.

Simplity Professional Services had to prepare methodology ready to analyze and examine which data were relevant to use. To do this we had to solve the following challenges:

  • How to perform market basket analysis when there is no “basket” due to nature of the financial products. In this case services cannot be wrapped into one single basket because the customer buys them one by one at separate times, not as product bundling at one given moment.

  • Which data to use for the market basket analysis so that it is relevant.

  • What questions to ask during processing market basket analysis, so the result is relevant to

Project in numbers is an online insurance, investments, and mortgage comparison portal focused on client online services. Within the DRFG Group it plays a significant role with its 2.5 billion Crowns turnover. The online portal was launched in 2008. The market basket analysis performed served as a basis for cross-sells, upsells, and campaigns in CRM. It also confirmed some of the management ideas and helps to further develop’s market strategy.




Product groups


Turnover in Czech Crowns (CZK)


Brokers selling more than one product


Confirm sales strategy and increase sales wanted to confirm whether their strategy was in line with the data or not, which data are missing, and provide sales and CRM teams with insights concerning cross-sells and upsells.

Solution data department exported and consolidated over 7,000 contracts with 40,000 customers based on requirements outlined by Simplity.

Working with, Simplity then helped define the market basket analysis. This was not easy as is a company without natural grouping of sold products into single orders (market baskets). We provided a concept based on scanning the sales timeline and grouping sold products into dummy market baskets. Dummy market baskets are calculated with consideration of a time frame between single product sales, which is carefully analyzed and set in cooperation with

During this profiling step, in conjunction with, we developed 18 specific questions. We were able to deliver answers to 15 of these because 3 of them lacked the data to be able to perform the analyses. The questions were mostly related to how products are sold together, what is the difference in data for each broker group with focus on a specific product, what is the difference when selling product groups for each broker group, and how much money brokers lose when not selling products from the whole portfolio.

All’s contract data were grouped into categories, compared to each other over a two year period and, based on data from the profiling step, Simplity defined a 90-day period to be used as a market basket, as 70% of the purchases were done in such a buying window.

Then we conducted market basket analysis based on antecedent and consequent products sold. Results of the market basket analysis were:

  • Market basket analysis chart comparing 10 products groups and how the products are sold together (for instance, association rules for mortgages and property insurance, or life insurance and liability insurance, etc.).

  • Simplity confirmed which category combination is the most promising along with which additional, other categories might also be promising. This gives valuable insights into what products brokers should offer for cross-sells to increase sales and customer lifetime value (CLTV).

  • Simplity identified that for better results more time stamps when a broker interacts with a client are needed. Brokers should properly track these data immediately after interaction with clients in CRM.

  • Simplity suggested that the broker group should implement recommendations from the analysis as next best offer suggestions for brokers into CRM. This way, brokers get notified about possible cross-sells and when to contact the client in the best buying window.


The market basket analysis for proved which products are best sold together. It also identified gaps in the data i.e., what data should be focused on for collection for future use. It has also confirmed, based on data, which is the most promising service category to cross-sell and that’s strategy is correct. is now working with Simplity’s consultants to help them choose a new CRM solution to make sure that data findings are taken seriously, collected, and utilized properly.

Additionally, Simplity is suggesting integration for the frontend and CRM data, so that can optimize solution costs and increase turnover, by an estimated 5%, via improved cross-selling and upselling.


What the client is saying

Simplity provided us with valuable insights about product affinities. We have added additional requirements in order to increase CRM effectivity. We have confirmed by data that our market strategy is right and what we need to improve in our CRM data and processes.

Jan Bartůšek, Director DRFG Financial Services

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