Check your assumptions at the door and collect customer clues for e-personalisation, says Kevin Ross.
Don’t judge a book by its cover, all that glitters is not gold, appearances can be deceiving – we sometimes forget the popular idioms advising us against jumping to conclusions or making assumptions. Instead, we can keep taking the path of least resistance and lose sight of exploring other options.
Just because a man walking down the street wears a t-shirt emblazoned with a rock band’s logo doesn’t mean he isn’t interested in purchasing suits. It’s most likely his weekend wear and if judged on that sole outfit, one might overlook that he’s a corporate player Monday to Friday.
Welcome to the era of personalisation.
In the digital age, marketers must be able to pre-empt customers’ desires, needs and behaviours. Essentially, they have to know who their customers are, where they are and what they want. Faced with all these unanswered questions, it can be easy to jump to assumptions based on a single data point or shallow data set. But customers aren’t one-dimensional characters and they can’t be captured with a single metric.
A recent report by EConsultancy in association with SDL revealed retailers place the most value on customer purchase history and digital behaviour when making predictions about their customers. This data may be useful when recommending products as the customer is shopping, but can be inadequate for developing a complete picture of who that customer is and building loyalty in the long term.
For example, a woman purchasing a men’s watch for her husband’s birthday isn’t going to want to receive notifications exclusively on watches during the next few months. Sometimes there isn’t enough information on previous purchases to determine whether customers are buying items for themselves or whether they are purchasing a gift – an issue exacerbated in Christmas season and other peak retail times. This is where additional information and data can help complete the profile of your customer.
The importance of good customer experience can’t be overstated as 47 per cent of respondents in EConsultancy’s survey said a brand is its customer experience. In the age of the ever-informed customer faced with so many options and alternatives, marketers can’t afford to make assumptions.
Simply going off purchase data doesn’t tell you enough about your customer and can lead you down the path of pigeonholing your customers. So what is the cure to tunnel vision? Collating demographic and behavioural data from multiple sources and touchpoints to develop a complete picture of your customer.
Most retailers are collecting hordes of customer data. Just think of all the places your customer engages with your brand: Instagram, Twitter, online and in-store, for example. Each of these platforms generate information about them.
Even a brand with an advanced content management system and sophisticated analytics software will fail to develop a complete picture of its customers if data from multiple touchpoints isn’t combined. Sure, look at a customer’s purchase history, but look at it in conjunction with their location, communications, profile (age, gender, profession) and spending habits. Meaningful patterns can be found via multiple touchpoints in both meaningful and seemingly meaningless noise.
By bringing additional data into play, you can determine that the woman purchasing a watch for her husband lives in a colder climate and may be interested in buying scarves, jumpers and jackets for herself.
Data analytics is the key to understanding customers’ behaviours, wants and needs. Marketers need to develop personalised approaches by piecing together data-driven insights and building a complete picture of each customer. Customers are leaving traces of data, digitally communicating to brands who they are. Brands need to open their eyes and ears, pull this information together and act upon it. Widen your lens, check your assumptions at the door and reap customer experience success.