Global
Customers now interact with brands in a variety of ways. They can shop at brick-and-mortar locations, talk with customer service representatives by phone, 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 manage customer data 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 and managing customer data well? Follow these fundamental steps to customer data management and ensure you are taking full advantage of all the information that’s accumulating from customer interactions:
Customer Data Management – 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 critical in managing customer database by aggregating 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 to manage customer data 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, you can manage business data, regardless of format and harmonize this data by mapping it to the industry standard Cloud Information Model (CIM).
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. To deliver the personalized experiences that today’s customers crave, you need to be able to anticipate their needs and deliver what they want before they even want it. Technology such as Salesforce Tableau can offer this level of advanced business intelligence and features accessible machine learning, statistics, natural language, and smart data prep. It’s a technology that allows companies to predict customer behavior better and automate personalized services that appeal to customers as individuals, not as a group.
Ensure the insights are used to improve customer experience
Done right, analytics generate actionable insights. But those actionable insights are only valuable if they are put to work to improve customer experience. Make sure the relevant teams, including marketing, engineering, sales, and customer service, can access the insights you’re generating and use 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 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.
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 manage 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 interact 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 costs.
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 can 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 take advantage of all the data your customers provide and that your decisions are indeed data driven.
