In today's environment, data is exceedingly important but also increasingly harder to get and manage. A reliable customer data platform (CDP) can provide significant value to retail and consumer packaged goods (CPG) companies.

Customer data platforms are used to consolidate and integrate customer and consumer data into a single data source. CDP technologies offer sales and marketing teams relevant insights needed to run more profitable promotional campaigns. A CDP can grab information from online and offline sources such as websites, mobile apps and email platforms to offer a complete view of the customer.

After retrieving this data, a CDP can then help organizations predict the optimal next purchase with a particular customer. Consumer products companies and retailers can then determine what they need to do in order to retain specific customers.

A comprehensive CDP can provide a 360-degree view of a customer, which can be used for campaign management, cross-channel analysis and multichannel sales and marketing hubs. This data can be analyzed and used to provide additional information that can improve demand planning. A CDP can be used to create more accurate forecasts of demand by using improved targeting of marketing campaigns, additional information regarding promotions, as well as consumer insights.

The facts around CDP technology

According to Forrester, automation CDPs build customer profiles, provide a campaign design interface, natively execute campaigns including email and mobile messaging and embed a decision engine to automate campaign orchestration. They also facilitate direct targeting via web personalization and product recommendations.

As an automation CDP, SAS has plenty of the “highest” rankings for capabilities that marketers need in today’s digital world. These include:

  • Developing a single customer view.
  • Personalizing content and offers.
  • Segmentation.
  • Data orchestration/egress for triggered interactions.
  • Egress/data orchestration for campaigns.
  • Data orchestration/egress for CX.
  • Testing.
  • Reporting and dashboarding.
  • Native execution of campaigns, personalization and profile management.
Want a more retail and consumer packaged goods (CPG) perspective on CDP capabilities? See the IDC Worldwide Retail and CPG Customer Data Platform Software Provider 2022 Vendor Assessment MarketScape.

What should you be looking for in a CDP for Retail and CPG?

According to IDC, if retailers and CPG companies want to achieve real-time contextual personalization, they must be able to integrate data silos and leverage AI and analytics. However, breaking down silos and dealing with privacy and security are also some of the biggest challenges that this industry faces. By 2024, 25% of customer data will be sourced from shared customer data hubs for personalizing experiences and improving omnichannel marketing, merchandising, and service intelligence.

A recent study from MIT SMR Connections highlights just how important real-time personalization and analytics are to retail and CPG companies. Nearly 50% are using personalization technology and are attempting real-time data collection and 33% are striving for omnichannel connected experiences. Retail and CPG are also among the leading industries when it comes to applying analytics to the various stages of the CX journey with 55% using them to a great or considerable extent in the product research phase, 60% in the purchase or adoption phase and 62% in the ongoing engagement phase.

Dealing with the constantly evolving data privacy regulations and limitations is also a big issue for the industry, particularly as analytically driven personalization gains in prominence. The impending loss of third-party cookies is a great example of this. For an industry so dependent on online customer behavioral data, losing the third-party data sources that provide much of this information will leave many companies scrambling to find the information they need to continue to provide effective analytics and contextual personalization.

Some of the capabilities that made a good automation CDP according to the Forrester Now Tech study and leader in the IDC retail CDP market scape include:

Ingesting data

  • Enterprise-scale data collection mechanism for 360 customer view.
  • Unparalleled granularity – user behavioral data from pages, screens and field interactions, across digital properties.
  • Data layer variable ingestion from virtually any platform (e.g., Google, Adobe).

Managing identities

  • Real-time deterministic identity management.
  • Digital events dynamically update identities.
  • Online and offline profile data support (with full control on how to append, delete and merge customer. identities).

Developing insights

  • On-premises and cloud segments.
  • Dynamically updated on-premises segments with digital activity.
  • Beyond simple segmentation – advanced models, clustering, targeting.
  • “Do it for me” options – segment discovery, etc.

Provisioning and activating data

  • Omnichannel journey orchestration.
  • Real-time send/receipt of third-party events.
  • Integration – decision engines, Adobe, Salesforce, display media platforms.
  • Algorithmic multi-touch attribution and customer journey insight.

Our CDP is part of the SAS Customer Intelligence 360 suite of products. It enables marketers to seamlessly extend and enhance customer data activation, addressing use-cases that go well beyond traditional customer data management.

Check out this short video to learn more on why companies are choosing SAS Customer Intelligence 360 as its CDP.

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About Author

Charlie Chase

Executive Industry Consultant/Trusted Advisor, SAS Retail/CPG Global Practice

Charles Chase is the executive industry consultant and trusted advisor for the SAS Retail/CPG global practice. He is the author of Next Generation Demand Management: People, Process, Analytics and Technology, author of Demand-Driven Forecasting: A Structured Approach to Forecasting, and co-author of Bricks Matter: The Role of Supply Chains in Building Market-Driven Differentiation, as well as over 50 articles in several business journals on demand forecasting and planning, supply chain management, and market response modeling. His latest book is Consumption-Based Forecasting and Planning: Predicting Changing Demand Patterns in the New Digital Economy. To learn more, please see his Author page.

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