4 Tips That Will Help Your Company Get More Insight Out of its Big Data

According to McKinsey & Company, executive teams that make extensive use of customer data analytics across all business decisions see a 126% profit improvement over companies that don’t. And those that champion customer analytics “broadly and intensively” as a whole company see 6.5 times more customer retention, 7.4 times more outperformance of competitors and almost 19 times more above-average profitability.

When you organize your company by unique customer lifetime value, you can make use of the segments and micro-segments that big data analytics have revealed and defined to maximize profitability, market share and competitive advantage. By targeting customers at the right time, with the right product mix, in the right way, you can gain the most value from every customer.

Here’s how to make the most of this readily available customer data.

1. Identify the data that matters. According to IBM, 90% of the data in the world today has been created in the last two years alone. And while your company may be better equipped to handle the influx of new data from a variety of sources, it also may be buried in meaningless data. What you need is a plan.

It’s increasingly important to get beyond the “gather everything and sort it out later” approach to big data, and instead track and capture the consumer-generated data that provides a direct value to your company. Look for a correlation between customer characteristics and buying behavior to see how your customers interact with your products and services and make a list of the big data that matters to your bottom line. Then work with your marketing and sales departments to make sure that every metric you ask them to capture represents accessible and actionable information.

2. Use metrics and segmentation to reorganize your customer’s experience. Request an analysis of your current data on your most valuable customers. Ask questions about which characteristics these customers have in common and which characteristics they do not share. Ask your chief marketing officer to group consumer segments according to their preferences to create clear lifecycle delineations for each segment.

3. Reorganize your departments by customer preference rather than product line and assign segment owners or leaders to each group. When functioning properly, the customer experience will be guided by the customer’s lifecycle need for each product rather than your brand manager’s need to meet a sales quota or goal. Then, using big data analytics, task segment owners with predicting shifts in the needs of the customers in their micro-segments and work with other segment owners to define the optimal new product that will capture the most value.

4. Authorize your marketing and sales teams to take calculated action based on insights gleaned. Have sales and marketing use the insights gleaned to develop targeted and localized customer value propositions.

One of the biggest challenge leaders face is in taking the leap toward customer-focused organizations from their current product-centric ones. However, big data streams and smarter analytics resulting from these data sources can facilitate the enablement of customer-centric organizations and inform the CEOs about the enormous value these new organizational structures can deliver.

By intelligently leveraging the power of big data CEOs can stay ahead of the curve and deliver sustainable competitive advantage for their organizations.