Shopping Cart AnalyticsIDP delivers data-driven marketing solutions like shopping cart analytics, with a focus on data integration, ‘invasive’ data management and deep-dive data mining.

What do consumers want in exchange for their loyalty? Lots and lots of attention., Feb 2017

The economics of loyalty programs continues to evolve. Today, selling products at discount to retain shoppers is not sustainable. And ensuring that discounts pay off is crucial to maintaining profits. Whether offering discounts to attract or maintain customers. So marketers rely on shopping cart analytics to not only monitor shopping behaviors and engage loyal customers, but to manage loyalty.

When loyalty involves bribery, it’s bad for business. Confusing loyalty with retention and rewards undermines brand equity more than it creates new opportunities. — HBR, Mar 2015

Shopping Cart Analytics — Benefits

Shopping cart analytics measure, among other things, customer responses to promotions and the value of market baskets. It’s not about what items sell, but what combinations of items and the profit from those combinations. So savvy marketers measure not only product and customer profitability, but the value of loyalty.

Retailers are wasting billions of dollars a year on loyalty programs as rewards points sit unused and consumers shift to rivals anyway. —, Feb 2017

Finding a shopping cart link between products and customers means one targeted promotion can drive sales in other categories. By examining responses to promotions and item affinities – together – marketers move beyond just analyzing sales. They’re unlocking marketable insights and growing basket spend without bribery.

Shopping Cart Analytics — Challenges

Shopping cart analytics are not rocket science, but require ‘invasive’ data management and deep-dive data mining. The analytics require transaction detail over a time period long enough to consider trends, and include complex interactions between customer and product. Because of data volumes and complexity, shopping cart analytics are beyond the abilities of all reporting tools and most business analysts.

One of the biggest roadblocks in creating personalized customer experience is the maze created by the various silos that exist within a company. —, Nov 2015

The challenge for marketers is using all their data to effectively engage customers. They’re challenged by both data volumes and velocity. Many aren’t sure of the data they have. They don’t believe they have the data they need; and what they have, they question the quality. Or they can’t access. Finally, business analysts, who aren’t trained to manage complex data, create error-filled or incomplete analytics. So marketers fail to get the insights they need, and lose confidence in both reporting and data.

Shopping Cart Analytics — IDP

Shopping Cart AnalyticsEffective use of customer data is a competitive weapon. So at IDP, Our goal is to help marketers control their data, their analytics and their marketing technology.

IDP removes the requirement that business analysts manage large and complex data volumes. We bridge the gap between data management and analytics. So analysts focus, not on data, but on analytics. We manage those large data volumes with complex structures. We integrate disparate data sources and build rock-solid analytical data sets.

Finally, we always collaborate with marketing to generate the right analytic methodologies that produce marketable results.

When the supporting data is rock-solid, then Shopping Cart Analytics become much, much easier!