5 Reasons Why a CDP is Core to a Retailer’s CX Strategy in the New Normal


Retail has seen dramatic shifts in customer needs, tastes, and behavior, and the pandemic has upended many tried and tested marketing tactics. Digital-first now is the new normal with in-person shopping forced to take a back seat, with much of this shift is likely to stick for a long time to come.

E-commerce share of the revenue pie in the retail industry has doubled and, in some segments, quadrupled as well. Albertsons, for example, reported digital sales growth of 243% for the second quarter 2020.  

Consumers spent $861.12 billion online with U.S. merchants in 2020, up an incredible 44% year over year, according to DigitalCommerce360 estimates. That’s the highest annual U.S. ecommerce growth in at least two decades. It’s also nearly triple the 15.1% jump in 2019.  

Insights of the 2008 financial crisis showed that companies that led with CX gained three times as much as the market average in terms of shareholder returns and rebounded more rapidly as well. The performance of these CX leaders during the financial crisis serves as a helpful guide for companies hustling to do business amidst the global pandemic today. 

Some retailers are better equipped to handle the shift in consumer behavior, while others are struggling between physical and digital realms. For those retailers who are looking to up their customer engagement game in the channel of their choosing, here is how the right customer data platform, or CDP, can be utilized as a powerful agent of change. 

1. Relearning Customer Needs, Tastes and Behavior

Creating a unified, 360-degree view of the customer that is also actionable is the most fundamental step in creating superior CX for customers. For example, sending two “personalized” emails to the same person is hardly that!

A CDP should be capable of ingesting heaps of data from a variety of sources — e-commerce, mobile app, stores, kiosks, CRM, ERP, DMP, etc., match, deduplicate, and fill in the gaps with any customer information that may be missing. While a lot of this is explicit data captured in other systems, advanced CDPs can also derive implicit insights, from search intent, affinities from prior purchases (such as brand and/or category affinity) and much more.

CDP can also analyze this unified customer data using advanced AI algorithms to create granular, look-alike micro segments of the “best customers” or households, and track and analyze customer segments and their migration as they happen, enabling retail marketers to drive personalized engagement throughout the customer lifecycle. 

Zara, the Spanish apparel retailer that specializes in fast fashion, has invested over $1 billion to boost its online game. Zara has consolidated its business through the use of big data by gathering information from online social media and surveys to understand customer segments. The information is then used to make fast predictions of customer needs, helping them meet customer demands more quickly than their competitors. 

2. Real-time Customer Engagement 

In marketing, timing is everything. Brands are required to communicate more often and especially at crucial journey “moments” or they end up losing the opportunity to mesmerize and capture their audience. Real-time CDPs provide real-time audience activation, which helps orchestrate relevant campaigns and communication before they leave your properties. Engaging with customers in the moment is a key differentiator that very few retailers can boast of, and a real-time CDP enables this. 

For example, quick service restaurants can send customized offers on their mobile based on customer location or day part. No more "10% off on Margherita pizza at Fremont" when the customer is miles away in San Jose!

3. Personalization at Scale 

CDPs have enabled personalization at scale, an area in marketing that is capable of adding $1.7 trillion to $3 trillion in new value according to McKinsey & Co. And brands are looking to unlock this potential. 

With deep knowledge of customers and personas provided by CDP, retailers can now activate a personalized 1:1 customer experience. Modern CDPs bundle advanced personalization module, which needs to be contextually sensitive and a continuous algorithmic testing engine, which ensures that the right decisions are being made automatically with every interaction in real time. From landing pages to the entire commerce funnel, retailers can ensure a highly relevant and engaging experience, improving both customer satisfaction and conversion. 

With machine learning-based algorithms for demand forecasting, assortment planning, store clustering, size pack optimization, product rationalization and discount pricing, retailers can ensure the right availability across all points of sale, including store and digital.

For example, QSRs could personalize the menu when the customer opens the app for placing an order. By using a CDP to analyze a customer's purchase history, it will be easy to infer if they are a vegan. Based on this, the most relevant menu items are listed on top of their menu. 

Latest innovations include deep learning-based recommendations, where retailers can replicate the rich in-store experience digitally with advanced Visual AI and text/NLP-based personalization in real time, mimicking human-like curation.

4. Data Security And Privacy Compliance 

Building trust between the brand and the customer is a business priority. With GDPR and other regulatory requirements around customer data privacy and security becoming mandatory, CDP helps manage known and unknown PII data and consent to comply with these norms.

The laws and regulations surrounding data protection has made first-party, consent-driven data collection more important than ever for companies. 

5. Align Demand with Supply

Perhaps the most important, but most retailers are unable to link their CDP to the core of their retail business. They continue to treat this investment as another silo, except for the marketing team. A retail-focused CDP brings together demand-focused data, and combines with customer-centric merchandising and buyer planning.

With machine learning-based algorithms for demand forecasting, assortment planning, store clustering, size pack optimization, product rationalization and discount pricing, retailers can ensure the right availability across all points of sale, including store and digital.  

Pandemic or not, the next normal is still taking shape, and like your grown kid who refuses to move out, digital is here to stay with us for the long term. Retailers who invest in CDP technologies will drive differentiated CX across channels, accomplish the delicate balancing act of optimizing for immediate conversions as well as long term customer value.

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Raj Badarinath is the CMO at Algonomy, where he’s enabling retailers and brands to compete on memorable digital experiences.  

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