Data is worthless if it’s not used. The problem is, many marketers don’t know how to analyze data or fail to do anything with it. 

In my experience, data is typically organized the way companies are organized — siloed within each organizational unit to support that unit’s goals, priorities and deliverables. Segregated data means the company is operating with only a partial view of the customer. Without a holistic view, companies are unable to see patterns and develop actions to facilitate an easier and more effective customer journey.

Companies also don’t know how to make sense of the data. Analyzing data is a challenging task. eBay has Jurassic Park-sized data challenges. The company produces 50TB of machine-generated data daily that is accessed by 7,000 analysts with 700 [concurrent users]. Asking a simple question like, “What were the top items that showed up in searches yesterday?" involves processing five billion page views alone.

Even if you’re not a B2C company or the size of eBay, it’s important to have data scientists or dedicated people who are committed to analyzing various sources in order to create personal experiences around what you know about the customer.

Analyze, Test, Iterate

Once you have the data, you need a plan to maximize it. I advise my B2B clients to tackle one problem at a time, solving it across the entire ecosystem. 

Take a particular product: How will you leverage data to increase your profits around this product? Start with an in-depth look at the end-to-end process. You might pick one persona and use the data to understand where the process breaks down and where the process works. Adjust the experience to fill in the gaps and allow for better conversion rates. Most importantly, use the lessons learned and find automated ways to scale the process then apply these lessons and methodologies to other products over time.

This is exactly the approach my company is implementing with one of our B2B clients. The company was looking to leverage the overall customer journey data to optimize the experience for its customers and increase conversions. Its customers typically have a long selling cycle and touch multiple digital properties during their purchase journey. This includes off-domain social, campaign pages, marketing site, commerce sites and many others. 

The client had captured a large amount of data, but the data was segregated by the different properties. The task of consolidating the data and personalizing the experience based on learning seemed daunting. But by picking one product and one persona across the properties, we reduced the data analyses to a fraction of the overall available data. This approach also made the effort of analyzing and personalizing the experience more manageable. The takeaways from this product will inform the approach to other products. 

Cross Sell and Upsell

A complete view of the data increases your opportunities to upsell and cross sell. Companies that offer subscription services, for example, can offer customers free subscriptions to other content for a limited time based on their current and past purchases. The conversion rate of making special and personalized offers is greater than if you did nothing at all. The effectiveness of those offers depends on data analysis and the entire journey, which is why a holistic view is so critical.

Create Better Products and Services

For many years people have used data to optimize campaigns and determine what campaign strategies are more effective. With the age of the Internet of Things, many products in the market are connected. Data is recorded daily and given back to manufacturers for analysis. Manufacturers should use this data to create better products based on the customer consumption data. In a way, the manufacturing customers are establishing the roadmap for the companies’ own customers. This is not a foreign idea, but now we have the hard data to support it.

Creative Commons Creative Commons Attribution 2.0 Generic License Title image by  Georgie Pauwels