Why intelligence trumps analytics in your customer retention strategies
Posted by Julian Diaz
February 16, 2016
Data has redefined how businesses understand their customer base and make decisions. For instance, it’s transformed marketing from a relatively intangible expense into a clear-cut investment with a measurable ROI and targetable initiatives. However, strategically applied data has more uses than strengthening your marketing efforts alone, especially when it comes to understanding your existing customers and better attending to their needs.
Data analytics capabilities, in particular, have blown up in recent years, giving businesses access to a far wider range of data-related insights than ever before. But it’s important to differentiate between vanity metrics – and genuinely actionable information that can further your business goals.
In this article, we’ll outline why data intelligence is far more valuable than basic analytics – especially when it comes to your customer retention strategies.
The difference between data analytics and data intelligence.
First and foremost, it’s important to differentiate between data analytics and data intelligence. According to Techopedia, data intelligence is “the analysis of various forms of data in such a way that it can be used by companies to expand their services or investments.” This is distinct from their definition of data analytics, which is the “science of examining raw data with the purpose of drawing conclusions about that information” according to TechTarget.
While these terms are inherently related, data intelligence involves a more specific and forward-looking use of data to reap deeper insights that can be used to grow the business and to get the most from investments. Where analytics identifies trends in your customer, data intelligence applies that information to craft an effective strategy that can be put into action in a realistic timeframe.
Your customer retention strategies need to be forward-thinking.
Data intelligence means using analytics as a vehicle to customer (and, in fact, business-wide) insights that facilitate action and positive change. This is vital in the context of customer retention strategies, as each strategic decision must be made with the future in mind – be it gaining customers that are more likely to stick around, pleasing existing customers or knowing which customers need extra attention to avoid losing them. Sure it’s interesting to know the satisfaction levels of certain customers at your company’s various contact points, but unless that data is being used to inform an action that can positively impact future customer satisfaction, it’s of little tangible use – your metrics need to work for you. This point is highlighted in a great article by Forrester, where the research firm predicts that companies who make customer satisfaction – and thereby customer retention – a focal point will shine in 2016. And to do this, it’s crucial to close the gap between the insight of data analytics and the action needed to make positive change.
So you understand the value of using data in you customer retention strategies, but aren’t sure how to go about evolving your standard analytics into next-level intelligence? It’s a fair question. Beyond recognising the need for data intelligence, perhaps the most important step is to invest in a data analytics solution that combines machine learning and predictive analytics.
There are a number of key processes that can help you predict customer behaviour and act accordingly. For example, by combining data from previous customers that have left with that of current customers, machine learning can pick up on tell-tale signs of a customer that’s about to leave the brand and let the company know. This makes you better equipped at anticipating defection from your service or programme and sending an offer that gets a customer to stay. Doing so increases overall customer security and lowers the rate of attrition, as well as providing key insights that can supplement your on-boarding process to help build stronger customer relationships right from the start.
Contact us to learn more about how data intelligence and data analytics can boost your customer retention strategies and how, in partnership with Principa, you can make your data work wonders across various areas of your business.
Julian Diaz is Head of Marketing for Principa. American born and raised, Julian has worked in the IT industry for over 20 years. Having begun his career at a major software company in Germany, Julian made the move to South Africa in 1998 when he joined Dimension Data and later MWEB (leading South African ISP). Since then, Julian has helped launch various South African technology brands into international markets.