Often marketers like to think they know what their customers want, but no matter how seasoned and talented they are, it’s just not correct to believe so. We live in a dynamic world and the average customer is ever-changing their likes, dislikes and purchasing behaviour.
The truth is however, sometimes the customers themselves don’t know what they really want.
What Steve Jobs, Henry Ford and Phil Libin told us about asking what customers want can help us begin to understand this better.
“It’s really hard to design products by focus groups. A lot of times, people don’t know what they want until you show it to them.”
– Steve Jobs
“If I had asked people what they wanted, they would have said faster horses.”
– Henry Ford
“Customer feedback is great for telling you what you did wrong. It’s terrible at telling you what you should do next”
– Phil Libin, CEO of Evernote
The Institute of Decision Making published an article explaining why customers aren’t good at telling you want they want, or what may influence them, especially in traditional research situations as follows:
• Research makes people pay more attention than they do in the real world
• We’re not as rational as we think
• If people think they are going to have to explain a choice, it affects the choice they make
• What people say they like can change
So, how can you find out what customers want without directly asking them? Well, follow their footprint.
Customers leave their footprint as they interact with your brand
Every interaction a customer has with a brand provides information about them. For example, POS data (what, when, where they buy), social media data (what do they say about your brand?), and multichannel touch points (how they respond to your ads/campaigns) – you can analyse this data to understand what customers want before they do.
It’s not just about implementing customer data analytics
Based on Forrester’s latest report “Asia-Pacific Companies Embrace Customer Analytics”, less than half completely trusted the data quality and analysis results of their company’s business intelligence applications, while 17 percent had little or no trust in these capabilities.
The report also puts emphasis on brands that fail to translate customer insights into business action. Those who do build their marketing tactics using data analytics tend to focus on customer segmentation and campaign performance measurement, but fail to recognise the importance of looking at the whole customer lifecycle.
Making customer data count and predicting their next move
As the expert for your product or service, it’s your job to show the customer what will best fit their needs. You can’t do that if you only focus on using data for customer segmentation and campaign management.
The first step to predict your customers’ next move is to understand whatmotivates them – how they use your products, what job your product or service is hired for, and what their hesitations and concerns are. The insights generated from the customer data should enable you to optimise marketing campaigns based on the margin or long-term value by customer and prospect.
Take HotelClub as an example, the leader of online hotel booking uses big data to understand a customer’s lifetime value to the company. They compiled data over a six-month period to map out the customer journey to create a model for predicting a customer’s value. From the analytics, they learnt that customers who had a good experience on trialling a product, came back to the site and increased the length of stay; so the value was higher. By leveraging customer data to understand the retention lifetime value of individual customers by estimating their future worth, helped HotelClub to understand whether they should spend 15 minutes, 20 minutes or an hour to retain a customer because they know if a customer is most likely to book with them in the future. With the model, HotelClub’s call centre can determine how much time should be spent on on-boarding and assisting customers who call in, versus directing them to other channels for information.
Brands fail to meet marketing ROI, if they only take data analytics as software to analyse the customer data for segmentation or generate insights that are just FYIs but not actionable.
If you ask customers for feedback, integrate them into the centralised data
Even though we can predict what customers want without asking them, we still should obtain their feedback. For one it validates our original set of hypotheses and more importantly, it gives us a more dynamic look into a customer’s mind. This way we can weed out all discrepancies.
Customer feedback can also tell you what they are happy or unhappy about, and thus is extremely useful to consistently improve products or services.
So if and when you are going to gather customer feedback, it is important to integrate this new data back into the complete database. You have to listen carefully to customers who tell you what doesn’t work as, Bill Gates once said, “Your most unhappy customers are your greatest source of learning.”And that is still true. However, without integrating customer feedback into data analytics approach, it’s just an FYI insight, and barely actionable. And an insight that isn’t actionable is a wasted treasure.
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