A woman in her 40s reclines on a grey velvet chaise longue in the Womenswear department of a well-known Oxford Street retailer, surrounded by a vast selection of shoes, bags, dresses, coats and scarves.
The store’s personal shopper discretely buzzes around her, holding fabrics in an array of colours against her face to assess how they complement her skin tone.
“This asymmetric hem will really flatter your shape… this shade of blue brings out your eyes… not everyone can wear these Manolo Blahniks, but you’ve got the confidence to carry them off… and you’ll be able to wear them again with the outfit we’ve picked out for your sister’s wedding in July…”
But this type of bespoke personal shopping experience is no longer the preserve of the well-heeled. Any company in any sector can now use big data analytics to forge personal connections with their customers and precision target them with exactly the right product at exactly the right time.
When we shop online or interact through social media, every one of us leaves a digital footprint. Big data analytics enables marketers to understand individual customer footprints and really get under the skin of each consumer through detailed profiling of their personality traits, analysing their online and offline behaviours and making accurate predictions regarding life events and spending patterns.
By treating each customer as an ‘individual’ rather than a ‘demographic’, companies can personalise their marketing tactics beyond general assumptions built on the traditional data currently available to them, such as gender, age, ethnicity and location. No decision based purely on traditional data is ever fully informed, and by doing so companies risk making inefficient decisions and ultimately losing money by simply not knowing their customers well enough
Marketers have long been targeting consumers by demographic but this doesn’t give enough insight – just because they’re female doesn’t mean that they love handbags and shoes, just because they’re 17 doesn’t mean that they’re in the market for a car, just because they live in Cardiff doesn’t mean they support Cardiff City.
Personality testing is becoming the ‘new demographic’ for marketers. Assessing consumers’ personality types through social media analytics can actually reveal exactly how they need – and want – to be approached by brands. For instance, certain personality types significantly prefer particular colours and appreciate aesthetics. Some love to plan ahead so need inviting to events months in advance while others are spontaneous so a last minute invite will be the most welcome approach. The more ‘rational’ consumer loves information and can be won over with statistics and competitor comparisons. The more ‘agreeable’ consumer dislikes ads which make comparisons as they don’t make quick decisions.
An ad striking the right message of “I know just what you’re thinking” rather than “I’m just targeting every female between the age of 25 and 35” can be the difference between a positive user experience resulting in a conversion and a negative user experience resulting in your brand being perceived as annoying and clueless.
Targeting ads using insights into consumers’ actual character and lifestyle not only improves conversion and click-through rates, it will enable businesses to save money by eliminating advertising to consumers who are unlikely to respond to your products, allowing businesses of any shape and size to benefit.
Using big data analytics, businesses can discover an individual consumer’s likes, hobbies, lifestyle and personality, combining this with traditional demographic data to refine segmentation further and target consumers with products and services that they really care about and market these to them in the right way at the right time.
But how is it done and can it really replicate the kind of bespoke service you receive from a personal shopper? At Hello Soda, our PROFILE platform takes thousands of data points from consumers’ digital footprints and generates scores for each of the Big Five personality traits (Openness, Conscientiousness, Extraversion, Agreeableness, and Neuroticism.) Using psycholinguistics, Bayesian Belief, machine learning, and natural language processing, we deliver real-time, easy-to-use scores directly to businesses.
By taking into account the Big Five personality traits, you can identify strategies to improve the effectiveness of marketing campaigns by gaining insights into a person’s lifestyle, earnings, online shopping activities, how they prefer to be contacted, when they are most online and even their preferred ad layout. Categorising customers by personality can help not only to understand their needs and motivations, but also how the products should be sold to them.
But – unlike the personal shopper – we can build and assess this “fabric of life” information in seconds on a consent basis, without needing long conversations with the customer about their social calendar and favourite shade of blue.
Developments in advanced big data analytics are giving marketers an insight they’ve never had before and will revolutionise the retail industry.
Just as the personal shopper needs to build relationships and understand their customers’ individual preferences and personalities as well as their budget restrictions, it is also vital for marketers to gather all information available to them to further personalise the shopping experience online. If they choose to ignore the wealth of customer data on offer, they are effectively choosing to shut the doors on their own customers.
