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Leveraging data analytics for SMEs
Economy November 28, 2018 01:00
By SPECIAL TO THE NATION
Based on the state Office of Small and Medium Enterprises Promotion (OSMEP) statistics, only half of the 700,000 newly established SMEs are able survive their first year. One of the critical reasons for this is their lack of marketing capability, according to TMB Analytics study.
HAVE YOU ever wondered why the survival rate of SMEs is so dismal?
SMEs usually focus on the production aspects of their business, while neglecting building brand awareness and customer engagement.
One efficient and effective way to improve this is by utilising data. The method is not exclusive to only large corporates – SMEs can also take advantage of this data. We are not talking about new or private customer data, but rather suggesting to begin with just the run-of-the-mill data that firms already possess but have not yet fully utilised.
This is crucial for survival of the business as customers’ characteristics and needs are becoming more and more expansive and varied, compared to the past when your customers were mostly your neighbours or people you were familiar with. It is even more critical for online businesses to understand their customers through data analysis because they rarely have face-to-face experiences with their customers.
For example, to understand your customers’ individuality, business owners can collect customers’ transactional data to learn their purchasing behaviour. Who are the majority of the customers? What are the products they are most interested in? How much have they bought? When will they repurchase the product? Where did they purchase the product? Answers to these questions could steer the marketing campaign in the right direction.
To elaborate further, let’s look at PetCareRx, the online US pet pharmacy, an example of SMEs successfully enhancing their marketing scheme by leveraging a simple data analytics method.
PetCareRx’s customers repurchased different products with different time lapses. For example, a customer may purchase dog health supplements every two weeks, while another customer may want to stock up and buy a larger quantity every two months. As a result, PetCareRx found it hard to establish an effective promotion or discount campaign that can apply to all customers at the same time to boost their product sales.
By using customers’ transactional data, such as their frequent purchase period, purchase frequency, and amount, PetCareRx is able to predict individual customers’ propensity to buy at a different point in time. They turn their promotional campaign around. Instead of applying the campaign to all customers at once, they nudge only the customers who are less likely to buy in order to encourage them to spend more. Using this targeted marketing method not only doubled the campaign response rate and boosted their sale by more than 24 per cent but also reduced the campaign advertising cost.
However, let’s not forget that before analysing data to find insights, firms have to start with correct and organised sets of data. Therefore, systematic collection and organisation of the incoming data is vital. This may not seem useful in the initial stages, but organised data will become the firms’ great assets for the forthcoming future. The procedure should be viewed as investment that will drive the businesses in the future. As said by Clive Humby: “Data is the new oil”.
Not only can basic data analytics tools be employed by SMEs or even artificial intelligence, the technology we assume to be inaccessible to normal firms can as well be utilised by SMEs. We will explore deeper into SMEs and AI technology in the next column.
Views expressed in this article are those of the author and not necessarily of TMB Bank or its executives. Biz Insight is coauthored by Nuttapong Netjinda and Tospol Kawsombutwattana. They can be reached at tmbanalytics@tmbbank.com
