Predictive analytics delivers marketing edge
Speaking at a SAS Integrated Marketing Management forum hosted recently in Nairobi, SAS experts highlighted numerous ways in which effective data management could improve service and business bottom line throughout the customer lifecycle.
Edward Sungura, SAS regional sales director for sub-Saharan Africa, stressed that analytics delivers significant benefits to businesses of all sizes. "The limitations in analytics are not due to the size of a business. The only limitations are related to the quality of the data available," he said.
Malcolm Lighthouse principal product manager for customer intelligence at SAS, said predictive analytics is not being fully used by enterprises around the world. "People need to do more of this," he said. "This is the single biggest way companies can differentiate themselves from the competition."
Find the customer, find the profitable customer
Lighthouse elaborated: "With effective use of predictive analytics, companies can not only identify their best customers, they can also identify which of them are most likely to behave profitably. By building predictive models in line with campaign strategies and overall business strategy, you can score customers and identify those customers most likely to be profitable to you, thus allowing you to double the profitability of marketing campaigns by eliminating non-responders and so eliminating the waste."
Alexander said to maximise marketing, companies need to define a strategy, then segment the customer base, identify the properties of each segment, set objectives for each segment, define the activities for each segment, and continually measure outcomes and refine campaigns.
"Predictive modelling gives you a rational basis for making decisions and helps ensure the success of marketing activities. Randomly targeting people for campaigns gives a far lower success rate," he said. He noted that SAS had brought to market a range of solutions to support integrated marketing management using advanced analytics.
Emergency airtime credit
Also speaking at the forum, Claire Munene, Head of Department Customer Value Management at telecoms market leader Safaricom, said effective use of analytics had enabled Safaricom to step up its customer retention initiatives and bring to market solutions customers needed. "While our recent results may show a slowdown in new customer acquisition, we still see strong revenue growth. This is as a result of our using customer intelligence tools to better understand our customer segments and target them with campaigns and solutions they need," she explained. As an example, Munene highlighted Safaricom's emergency airtime credit, a product launched after analysis of customer behaviour showed that many prepaid customers would use their phones a great deal, and run out of airtime late at night. They would then top up at around 09:00 the next day. "This told us that they talked until they had no airtime left - so they had the desire to talk for longer, but there were constraints in terms of purchasing airtime. As a result, we introduced the emergency airtime credit bundles, which are seeing good growth."
Lighthouse noted that with the amount of available data growing at an exponential rate, organisations need advanced tools to explore it, to find the 'needles in the haystack' that enable them to make better business decisions. "We think that in the long run, the business winners will be those that bring all the data together and optimise its use, to improve their systems and product offerings and create an overall better customer experience," he said.
About SAS
SAS is a leader in business analytics software and services, and claimed to be the largest independent vendor in the business intelligence market. Through innovative solutions, SAS aims to help customers at more than 60,000 sites improve performance and deliver value by making better decisions faster.
SAS was included in independent research company Forrester's "The Forrester Wave: Big Data Predictive Analytics Solutions: Q1 2013" report as a clear leader in the predictive analytics environment.
