Turn data insights into customer excellence.
By Barton Goldenberg
The buzz in the CRM industry is about big data. This data may come from your back- office ERP systems, your CRM system, social insights, or third-party sources.
At the end of the day, all that counts is your ability to use this data to make more informed decisions. But between raw data and informed decision-making is the all- important step of data analysis. Enter two challenges: the complexity of existing data analysis tools and the availability of data subject matter experts who can present insights to sales, marketing, and customer service executives. My forecast: In 2013, we will see tremendous enhancements in both areas, with data-driven decision-making becoming the norm, not the exception.
While companies such as Amazon and Sysco have excelled in the use of data analytics and predictive modeling, data-driven decision-making is no slam dunk. ISM works closely with B2C and B2B companies that have made data-driven decision-making part of their DNA. Each has set up an appropriate data structure (including, in several cases, data marts), has ensured that valuable internal and external data find their way into the data mart, and has engaged data analysts to cleanse, mine, and actively interpret the data to drive marketing and sales campaigns that deliver results.
One hospitality client has an amazing capability—using effective analytics and predictive modeling tools—to predict which customers should be approached for their credit card. A food service client uses analytics and predictive modeling to target customers with the next best offer based on the highest probability of success to close the deal. I have always been amazed that Nike knows its B2B customers (stores) and consumers so well that it can effectively recommend what a store should be purchasing from Nike. The stores love the advice, and Nike reaps the rewards of enhanced growth. Using similar data tools, many AAA clubs can spot which members are likely to churn and proactively intervene to avoid losing them. We have several clients leveraging data analysis and predictive modeling to segment their customer base and help ensure optimal customer journey moments of truth.
Most of these companies integrate these data insights with their CRM systems. This includes attaching customer insights to customer profiles, creating targeted marketing and e-commerce campaigns, better servicing customers via the contact center or self-service, and making real-time offers via the Web. While some CRM systems include meaningful data analytics tools, all provide the foundation to turn data insights into sales, marketing, and customer service excellence.
If you’re keen to jump onto the data-driven decision-making bandwagon, here’s what you’ll need to get right:
Data quality. Take an inventory of the customer data you have and its quality. Make corrections to alleviate data quality issues. Supplement data with third-party data sources (demographics, behavioral, lifestyle, technographics) for a richer understanding of your customers. It’s amazing what information is available; you’d be foolish not to use it.
Data analysis. Put your data analysts to work, or engage external data experts to come up with meaningful insights. This includes creating optimal customer segmentation and customer journey mapping, acquisition models, retention models, next-best-offer models, lifetime value models, creative marketing campaigns, and knowledge of who your sales reps should and should not call on.
Managerial training. Train managers and executives to use data for enhanced decision- making. Take steps to ensure that fact-based decision-making is a core value.
Measuring and monitoring. Data-driven decision-making is not a one-off event. With several customers, we are into second-, third-, or even fourth-generation data models that use quantitative (transactional) and qualitative (from customer interviews and surveys) data to provide deeper insights.
Computers do a brilliant job of crunching data and making sense of it. Our job as executives is twofold: to guide the data we want these computers to crunch and to play an active role in interpreting data insights.
This is the year for CRM data analytics, and there isn’t a day to wait to get started or to push your current efforts to a whole new level.
Barton Goldenberg (email@example.com) is president and founder of ISM Inc., a consulting firm that applies CRM, social CRM, and social media to successful customer- centric business strategies. He is the publisher of The eGuide to Mobile and Social
CRM (18th edition).