The next wave for Customer Data Platforms (CDPs)

Over the past few decades, the way organizations collect,manage and mine data has changed rapidly. The 90’s Customer Relationship Management (CRM) systems gave way to the 2000’s Data Management Platforms, which are now jostling with CDPs, for businesses’ attention. The case for CDPs became stronger, as certain shortcomings of legacy systems came to light:

1.      Little co-ordination among internal teams and external partners that collect/ provide data.

2.      Centralized, I.T.-controlled data hubs, barely in marketers’ control.

3.      Individual customers with unique needs, being clumped together under ‘Segment cohorts’.

4.      Customers switch seamlessly and quickly among email, web, mobile app whereas businesses are ill-equipped to connect email, web and mobile app environments in real time; hence unable to offer a uniform experience.

2019 saw the CDP conversation reach a crescendo, with Oracle releasing updates to its CDP (CX Unity). Typically, CDPs are tasked with data collection, data unification, data activation and data insights. They would include user-level data from customer databases, advertising/ marketing automation platforms and real-time customer service/ support.

Today, over 100 CDP companies’ offerings straddle the spectrum between insight and engagement. Some CDPs are built to discover new segments, build predictive models etc. (INSIGHT); whereas others allow marketers to deliver real-time personalization (ENGAGEMENT).

Industry majors like Adobe, Sales Force, Oracle have been in various stages of product development stage and are believed to have gotten product design right by now. These are default choices for large enterprises who trust big tech brands. That leaves a large area of play for other CDP players.

What are the big 3 in CDP, doing differently today?

A key realization that CDP majors have had is about data storage. This occurred due to growing recognition of data use-cases that require trend analysis and customer tracking basis historical data. Originally,CDPs were built around zero need for data storage and were designed to process all data ‘on-the-fly’. Of late, the growing number of commercial use-cases for historical data forced CDPs to take data storage more seriously.

A typical CDP offering’s promise would now look something like this:

Customer Data Platforms today

What this means for the Analytics ecosystem

Analytics sits bang in the middle of a CDP’s promise. Traditional models of outsourcing Analytics are primed to fail, in this brave new world. While certain CDPs claim to offer ‘in-built analytics’; business users’ learning curve will improve only once more and more businesses adopt CDPs.

Meanwhile, Analytics service providers will play the collaborator, trainer and decision-enabler roles. This is because of various advantages that standalone Analytics service providers can bring to the table:

·        Cross-domain exposure. Analytics companies have proven credentials working with all kinds of industries, data-sets, data integrations and data connectors.

·        Talent ownership. Despite the explosion of the Analytics space, most businesses struggle to attract and/ or find the right fit for their Analytics objectives.

·        AI & ML can get demanding to deploy. Addressing common marketing challenges like ChurnMicro-segmentation, prescriptive customer analytics or Hyper-personalization is complex. A CDP’s machine learning library might promise multiple benefits, but delivery of those benefits might require resources well beyond a business’ budget.

·        Tech deluge. Studies say that on an average,businesses use 7 or more technologies. Adding a CDP to such a ‘heavy’ tech stack simply magnifies data complexity, which businesses may be ill-equipped to handle.

·        Shift toward Predictive/ Prescriptive Analytics.Service providers are perfectly poised to apply their Data Science talent to equipping businesses with what will happen next. CDPs will need to evolve to feature automated data science capabilities which will enable the CDP to provide recommendations and personalization based on the context and intent of each customer at the precise moment.

Today, CDPs are being touted as the next best thing after DMPs. The focus is on the product (CDP), not so much the process or people required to make it successful. However, the next decade is likely to see businesses taking a step back from Tech and spending their energies on the People angle, instead. This would mean identifying trainers, collaborators and partners to help maximize adoption and regular usage of CDPs within the business.

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