4 Key Steps to Using Customer Data More Effectively

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Read more about author Vipul Taylor.

Customers now interact with brands in a variety of ways. They can shop in person at brick-and-mortar locations, talk with customer service representatives by phone, or browse, make purchases, and leave feedback online. Data is generated and collected at each one of these – and numerous other – touchpoints. But many companies do not know how to use this information effectively. The sheer volume of customer data pouring in can be overwhelming, as can the tangle of formats and systems. In fact, according to Invesp, a whopping 87% of marketers consider data their most underutilized asset. 

Is your company making the most of the customer data it collects? Follow these fundamental steps to ensure you are taking full advantage of all the information that’s accumulating from customer interactions:

1. Create a single source of truth 

With so many different touchpoints, it’s no surprise that customer data is captured in multiple disparate systems. But if that data stays trapped in those silos, you cannot develop a full picture of your buyers. That is why it is so critical to aggregate all of your customer data into a single, scalable customer relationship management (CRM) platform. Then, that CRM platform can serve as a single source of truth. For example, Salesforce CRM organizes data to provide a complete record of customer preferences and behaviors, from their online browsing habits and public social media activity (likes and dislikes) to their purchasing histories and outstanding customer service issues. The Salesforce customer data platform (CDP) takes it a step further by allowing companies to connect data sources from multiple sources, including from within Salesforce, Marketing Cloud, and external data sources, such as AWS, Azure, Snowflake, and Google Cloud Platform via MuleSoft. That way, all of the data, regardless of format, can be harmonized by mapping it to the industry standard Cloud Information Model (CIM).

2. Apply advanced analytics

Understanding what your customers did in the past – what they preferred and how they behaved – is only the first piece of the puzzle. In order to deliver the personalized experiences that today’s customers crave, you need to be able to anticipate their needs and be able to deliver what they want before they even want it. Technology such as Salesforce Tableau platform can offer this level of advanced business intelligence and features accessible machine learning, statistics, natural language, and smart data prep. It’s technology that allows companies to better predict customer behavior and automate personalized services that appeal to customers as individuals, not as a group. 

3. Ensure the insights are used to improve the customer experience

Done right, analytics generate actionable insights. But those actionable insights are only valuable if they are put to work to improve the customer experience. Make sure that all the relevant teams, including those in marketing, engineering, sales, and customer service, can access the insights you’re generating, and that they are using them as part of a comprehensive, coordinated strategy. Your marketing organization, for example, can use customer data insights to create new content, segmenting campaigns to enable a personalized journey full of the right content at the right time. This approach might include entering new customers into a campaign that automates specific messages, such as welcoming them and then sharing other products or services they may be interested in. These touchpoints can happen dynamically across various devices, channels (website, chat/messenger, etc.), and locations to deliver a seamless experience.

4. Track progress and iterate to drive business value 

As you follow the steps above, be sure to measure your progress as you go, and then iterate to drive even more business value. When you use your customer data effectively, you’ll be able to not only elevate the customer experience, but also optimize customer lifetime value (CLV), convert more new customers, and bolster compliance. To illustrate this point, consider an over-the-top (OTT) video streaming service that offers various free and paid subscriptions, each of which prompts users to share demographics and viewing preferences. Once a user becomes an active customer, systems start collecting engagement data such as how they are interacting with advertisements, when and how often the mobile app is used, and purchasing details. Internal teams can use insights like these to convert non-paying subscribers to paying subscribers, reduce the churn rate of existing customers, and optimize customer acquisition cost. Data about the performance of these initiatives can be fed back into the analytics engine, creating a feedback loop that’s continually working to optimize results.

Ultimately, the goal is to build an ongoing system that is able to collect, analyze, and take action on customer data. Begin by consolidating and integrating the data across all external interactions so you can develop a 360-degree view of each customer. Then, apply advanced analytics to create the insights needed to inform strategy, campaigns, and personalized initiatives. Using this approach ensures that you are taking advantage of all the data your customers are providing and that your decisions are truly data-driven.

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