Your favourite food is ready. Yummy! It looks delicious. By the way, my favourite food is “kontomire” stew and “banku”. What is your favourite food? Whether you order your favourite food from outside or prepare it at home, you agree it requires certain essential ingredients – ingredients without which the food tastes unpleasant. That is what this article is about, except the favourite food here is profit – growing profit year on year.
Growing profit year on year requires several inputs: relevant product/service, competent management, skilled staff, excellent customer service, enabling economic environment, positive organisational behaviours, right organisational culture, et cetera. However, some are essential inputs just like the ones required to prepare your favourite food.
Marketing, data-driven marketing is one of the essential inputs for growing profits consistently. You are probably asking why. With a simple Google search, you gather hundred and one reasons why data-driven marketing is important to growing profit. Okay, I admit that I exaggerated hundred-and-oneth time in my previous statement. Nevertheless, the point is increasing adoption of mobile technology in our daily activities makes data-driven marketing all-important. To make sure, we are on the same page, what I mean by data-driven marketing is collecting, analysing, and generating insight from data (now big data) to offer personalised customer experiences.
data-driven marketing is collecting, analysing, and generating insight from data (now big data) to offer personalised customer experiences
At this point you are wondering when am I going to talk about the three requirements stated in the title of the article. Very soon! Let me tell you another reason why data-driven marketing is important. Marketing is a powerful tool; data is a valuable resource; in company specific cases, data is a unique resource. Guess what combining a unique resource with a powerful tool gives you. Agree or disagree, but I think it gives you competitive advantage. The marketing strategy possibilities of feeding custom-built machine learning algorithms vast customer data points is unfathomable. You can predict high value customers from their first purchase, you can understand why a customer segment prefers certain brands, you can predict which customer group is likely to churn by next week, you can identify which marketing channels bring in high value customers, you can identify your top performing products and brands, et cetera.
combining a unique resource (data) with a powerful tool (marketing) gives you competitive advantage
Now that you are out of breath from reading several “you can, you can” statements in the previous paragraph, let’s talk about the three requirements for implementing effective data-driven marketing. Explaining each of these requirements may cover three chapters in a book. Therefore, I will be as brief as possible.
What this system does is it enables you to build complete 360 degree profile on each customer. In order words, it enables you to know everything you ought to know about your customer. You know her lifetime value, her preferences, her average spending per transaction, her social media interactions with your services, her wallet size and your share of it, etc.
Often, when we (by we, I mean data-driven marketing junkies) talk about fully integrated systems for collecting customer data, point-of-sale terminal or customer module of enterprise resource solution comes to mind. However, these are not fully integrated to paint a total picture of the customer. A decade ago, building and deploying integrated customer relationship management (CRM) solutions required huge investment. Today with cloud computing, you can simply deploy off-the-shelve solutions from Salesforce, Zoho, Agile one, Microsoft Dynamic, or from a boutique CRM service provider like Wave-2 Analytics. Full disclosure, I work with Wave-2 Analytics.
At this point, it is assumed you have in place a CRM solution which provides complete, cleaned, and relevant customer data and ready to generate some insight.
Fundamentally, the tools that enable insight generation from data cut across the entire spectrum of data analytics. So I am talking about tools for descriptive analytics, diagnostic analytics, predictive analytics, and prescriptive analytics. Read more about these types of analytics here.
Armed with a spreadsheet and free statistical packages, you may carry out descriptive analytics and some diagnostic analytics. For instance with descriptive analytics, you may know average sales per customer, number of customer transactions within a given period, your most profitable brands, etc. With diagnostic analytics, you may understand certain customer behaviours like why certain customers only patronise your services during sales promotions or why the value of sales per customer keeps decreasing.
To reap the full benefits of data-driven marketing, you need to go a notch higher to deploy tools for predictive analytics and prescriptive analytics. This is the arena where marketing superpower resides. Here we are talking about off-the-shelve or custom-built machine learning algorithms deployed not only to understand why sales per customer is declining, but also to predict the decline before it starts. The prescriptive capabilities of some of these systems are so advanced that they offer suggestions or solutions.
Again, the power of cloud computing has made it easy to deploy predictive analytics and prescriptive analytics platforms effortlessly and within budget. Find a comprehensive list of such platforms here . If you prefer a local vendor, kindly contact Wave-2 Analytics.
Here, we are talking about systems that connect the data to the marketing in order to arrive at the data-driven marketing. For example, if sales per customer is declining due to poor customer engagement, then you might consider systems that make it seamless for customer touch point agents to access the 360 degree customer profiles in order to have meaningful engagements with customers. Another example is that assuming through predictive models, you identified some new customers possess traits of high value customers, then you need a system to communicate this information to customer touch point agents to start treating these customers as VIP customers.
Often, companies new to data-driven marketing invest hugely in systems to collect data with little investment in generating insight from the data or leveraging the insight generated to deliver personalised services. This is known as the last mile problem. Simply put, overcoming the last mile problem is key to benefiting from initial investments in collecting customer data.
There you have it. The three fundamental requirements for implementing effective data-driven marketing. I hope you have connected the dots between the requirements and growing profit year on year. If not, this is it: through effective data-driven marketing, you delight customers with personalised experiences, boost revenue, and ultimately increase profit.
Elvis Agbenyega is the Country Director of Wave-2 Analytics. He combines his domain knowledge in business administration with data analytics to help businesses of all sizes deploy machine learning to understand their customers better and offer them personalised experiences leading to increased customer loyalty and revenue.