5 Customer Data Platform use cases you didn't know about
Why are CDPs important for Enterprise Retailers?
The most important reason why customer data platforms are so valuable for Enterprise Retailers is that they need to get to know their customers to understand what the best way is to approach them. Retailers must understand what their needs are and preferences and how they interact with your brand.
In a crowded market like today’s, customers are constantly being overwhelmed with information and advertisements from all types of products and services. To break through that noise and capture customers’ attention, leading retailers understand that the more personalized and targeted the communications are to what the customer needs, the greater the likelihood they will pay attention. Less is more.
Therefore, having high-quality customer data centralized into a CDP ensures cohesive and centralized customer data, that can be used for in-depth analytics and customer activation. In essence, it’s the basis for true personalization, so that you can reach your customers in the way they prefer, with the content they are most likely to be interested in.
Statistics around CDP Use Cases
- 96% of enterprises have a plan to adopt a “digital first” business strategy. (IDG 2021 Digital Business Study)
- 92% consider a CDP important to their privacy and compliance efforts. (Treasure Data, 2020)
- 74% of C-suite executives believe that good quality data gives them a competitive advantage over other businesses. (Treasure Data, February 2022)
- 65% of business leaders say their goal is to build a cohesive data ecosystem and to standardize data collection (CX Experience Report 2022)
- 63% say they are using customer data to influence product offerings while 43% say they are running a loyalty program that ties incentives to more than purchasing. (Treasure Data, January 2022.)
- 62% say marketing and 59% say sales departments are heavy users of customer data, but more than 40% are now using it for contact centers, supply chain/inventory management and product teams. (Treasure Data, January 2022)
- 63% marketers use a CDP to map out customer journeys and personalize digital campaigns (Treasure Data, 2020)
- 61% say that a CDP will be critical to their personalization efforts. (Segment, 2021)
- 81% of people are in favor of companies using AI to personalize recommendations. (CDP.com, April 2022)
Statistics around ROI of Customer Data Platforms
- More than 50% of marketers said ROI was achieved within 6 months and 80% saw positive ROI within 12 months. (Tealium, January 2022)
- 56% report positive financial impact as a result of utilizing customer data. The benefits are largely among organizations with 20,000 or more employees (84%). (Treasure Data, January 2022)
- 56.8% say they expect ROI of 5-10x from investing in a CDP. (Segment, 2021)
- 53% define ROI by cost savings as a result of implementing a CDP, while 58% measure ROI by sales and revenue growth. (Segment, 2021)
CDP Use Cases by Industry
|Industry||% Use Cases|
|Financial services & insurance||14%|
|Travel / Entertainment / Hospitality||3%|
|Logistics and Transport management||1%|
|Manufacturing / industrial||1%|
Focus of CDP platforms
The most common use case goals were customer value (cross-sell and upsell) and retention, closely followed by acquisition. These are all goals that relate to existing customers, which are usually considered the focus of CDP applications.
|Use Cases by Goal|
Source: CDP Institute Use Case Generator, 2021
A surprising 32% of users also listed awareness as a goal, but this was nearly always in addition to one of the other goals. Just 1% of the users listed awareness by itself. Similarly, while expense reduction was listed by 28%, only 4% listed it alone. Customer value alone accounted for 67% of use cases where a goal was specified, and 81% listed either customer value or retention. Nearly all (94%) listed customer value, retention, or acquisition.
KPIs frequently used to evaluate a CDP
These are the percentage of use cases with ease KPI
|% use cases with each KPI|
|Nr of customers engaged||64%|
|Number of sources||39%|
|Number of programs||39%|
|Batch processing time||30%|
|Number of access systems||29%|
Data Types Required
The most common data types are personal identifiers, transactions, and web behaviors.
|% use cases with data type|
|Intent & Interest||58%|
Most commonly used CDP capabilities
Looking across all use cases, the most commonly required capabilities relate to the most commonly required tasks: data assembly, followed by analytics and predictive models, and then by campaigns, interactions, and orchestration. But even the most common capability, building segments, is used by just 72% of use cases. Only three capabilities are needed by more than 50%.
|Tasks||Capabilities||% of all use cases|
|Measure results and optimize||39%|
|Data Assembly||Ingest Data||64%|
|Share data via API||42%|
|Analytics & Predictive||Build attribution model||42%|
|Append model output recurring||40%|
|Create data set||39%|
|Build predictive model||39%|
|Built lifetime value model||38%|
|Build recommendation model||36%|
|Append model output one-time||32%|
|Build affinity/ cross sell model||32%|
|Show performance in real-time||19%|
|Tasks||Capabilities||% of all use cases|
|Outbound, Real-time, Cross-Channel||Build content||36%|
|Built multi-step flow||36%|
|Build measurement process||28%|
|Send messages for external delivery||26%|
|Send messages directly form system||19%|
|Select best message across campaigns||17%|
|Define channels to use||10%|
|Select best channel||7%|
Most common use cases of a CDP
The most common use case of a CDP is data assembly.
This means that many CDP users see the primary purpose of their system as building unified profiles, which may then be used outside of the CDP. It suggests that the CDP can begin to deliver value as soon as the profiles become available.
Eventually, marketing campaigns and customer activation remain the ultimate goals for many users. The second and third most common purposes were outbound campaigns and realtime interactions, even though these come after analytics and predictive models in the task sequence.
Answers to the staffing questions suggest that the users who did specify analytics and predictive models often had in mind purposes outside of marketing, such as sales or customer service. These results reinforce that most CDP applications are within marketing and that CDPs have substantial use in other departments.
|Use Cases by Goal|
|Analytics & Predictive Models||22%|
Source: CDP Institute Use Case Generator, 2021
5 strategic CDP Use Cases for Retail Marketing Departments
1. Data governance strategy and compliance
Marketers need to have a strategy for data governance when using customer data to power marketing campaigns.
For example, can the marketing team generate a Subject Access Request (SAR) within the timescale demanded by GDPR? They might assume this will be taken care of by another team, but this is a function a CDP may provide.
Consent is an important ingredient of compliance and that doesn’t just mean opt-ins and opt-outs, marketers must show that consent was gained appropriately.
Marketers must operate within GDPR, CCPA and other regulations. GDPR applies to all personal data held on EU citizens. The CCPA, only comes applies where 50% of a company’s revenue is generated through data sales.
Having the ability to clean, match, deduplicate and merge data reduces the risk of data processing as it results in more trustworthy records, so if a consumer unsubscribes or opts out of emails they’ll be recorded as opted out of all emails, not just those sent through one email address.
2. Get consumer insights and give product recommendations
Retail marketers can use the CDP to analyze a customer’s purchase history and behavior and use predictive analytics data to better understand which specific products and brands sell most and to what segments.
This can be done by segmenting customers based on their purchasing patterns and targeting them with personalized offers related to their preferred products.
For example, a customer regularly buys a certain brand of lipstick from a retail website. Marketers can utilize this information and target her with real-time customized offers related to the product or other similar products.
3. Target customers based on intent and interests
A customer comes to a retail brand’s website with an intent to purchase a particular product but drops off. If this customer is a loyalty program member, the CDP instantly collects the browsing data and unifies it with previous purchases and behaviors. If this customer is a late night shopper, he could be sent a reminder in the evening to encourage him or her to complete the purchase.
If the visitor is anonymous, retail marketing teams can target the person through various online channels such as onsite and browser push notification. This could be achieved by tracking the anonymous user’s cookie via the CDP.
Alternately, when the user exhibits intent to exit the website, a lead form pops up, asking him to fill up his details. The user fills up his details and submits the form, as a result of which he can be targeted with specific, seasonal offers and incentives on channels such as email and SMS.
4. Go from online to in-store, and from in-store to online
Mapping a retail customer’s online shopping behaviour with offline purchases is the next big thing in enhancing customer experiences. A CDP can easily keep track of customer journeys and assist marketers in engaging users with the right offer in real-time.
For example, a customer visits a retail website and adds some items to the cart. However, he doesn’t complete the purchase and abandons the site. Later, he visits the brand’s retail store and instantly gets a mobile app notification with a personalized offer for the items that he had earlier selected online. How was this orchestrated? Simple: as soon as the customer entered the store, he triggered a geofence in real-time, which was recorded by the CDP. By looking at his past online activity, his offline experience was enriched in-store.
On the other hand, brick and mortar customer data can be used to personalize their website experience and encourage repeat purchases. Using the CDP, marketers can fetch a user’s store visit records and use that information for better cross-sells and up-sells.
For example, a customer purchases a PS5 from a retail store. To encourage him to continue his purchases, the brand fetches his preferred channel details from the CDP, in this case email and web notifications. The brand then targets the customer via these channels with customized online offers for PS5 games and accessories.
This kind of contextually-relevant offers resonate well with customers and generate huge growth opportunities.
5. Improve customer service and boost sales with real-time call center integration
Retail marketers can use the CDP to send out real-time triggers to a brand’s call center team when a prospect or a customer is on the website. This way, they can immediately call the customer, understand his requirements, and push him to make a purchase or visit a nearby store. This kind of real-time hand-holding will increase the number of online purchases as well as offline store walk-ins.
For example, a high-value customer browses a retail brand’s site. A real-time trigger is sent to the brand’s call center using the CDP. The call center representative contacts this customer and helps him find and purchase what he wants.
Conclusion: Top Tips for CDP deployment
The deployment and operational support Loyal Guru provides to all our clients has yielded important lessons around the use of Customer Data Platforms, specifically for Enterprise Retailers:
Lesson #1: CDPs can deliver value quickly.
The first use cases for most projects will be based on data assembly, which supports outcomes such as improved data quality and easier access to data for analytical projects.
Companies eager to demonstrate immediate return on their CDP investment should look for a few such projects that they can execute soon after their system is deployed.
Lesson #2: Engage all CDP users from the start.
Most CDP applications require a fairly small number of data sources, CDP capabilities, and delivery system integrations.
This simplifies initial deployment, but only if the right data, features, and connections are assembled. Selecting these requires tech staff and business users to collaborate in advance.
This collaboration needs to look beyond the initial use cases to understand which data, features, and connections will create the most value in the long run. It should extend to business users in all departments, even if they are not included in the early deployment stages.
Lesson #3: The transition from data assembly to applications requires careful preparation.
Applying the CDP will require cooperation from business users, who will often have little engagement with the CDP during the data assembly stage of deployment.
As a result, the CDP team will need to make special efforts to educate those users on what the CDP provides and how this can best be used.
Lesson #4: Deep, narrow deployments are most effective.
Organizations will get the most value in the shortest time by identifying an initial cluster of applications that require the same data sources, CDP capabilities, delivery system integrations, and users.
Once the system is set up to handle the first of these, the rest of the cluster can quickly follow. The deployment can then spread from this base, adding data, features, connections, and users in small batches and again taking full advantage of the new opportunities these create.
Loyal Guru provides the glue that connects all retail data sources (both online and at POS) with an API-based approach – no adhoc development necessary – and make data available across the entire organization.
We hope you are as excited as we are about the development of retail-specific customer data solutions and the opportunities that come from it, such as:
- creating single customer profiles with real-time, unified and enriched data from all online and offline sources, while managing constent, securing your data and complying with regulations
- leveraging the customer data you already collect, and upgrading your customer development strategies (with advanced campaigns to cross-sell, upsell, recover lapsing customers, foster loyalty and more)
- becoming more data driven, enabling business across multiple departments and boosting retail growth
Loyal Guru offers an unbeatable retail-specific CDP – and over 50 Enterprise Retailers across the globe have already upgraded their tech stack to leverage our solutions.
If you’re a retailer and you’d like to talk about any of the CDP capabilities or use cases outlined in this article in more detail, then get in touch with our team – we’ll be happy to show you examples or talk through your brand’s unique challenges.