Amazon and Shop Direct have been heralded for their incorporation of personalisation into their business – but what can the retail sector learn from others?
Personalisation, machine learning, artificial intelligence (AI) – whatever you call it, retail’s obsession with relevance and made-to-measure experiences for their customers has reached fever pitch in recent years.
However, are retailers’ efforts to better understand their customers really hitting the mark?
DigitasLBi strategy director David Carr says that what retailers call personalisation is often only slightly more than segmentation, and does little to actually endear themselves to shoppers.
“What if retailers could use the knowledge they have on their shoppers to help them accomplish their personal goals?”
“Great personalisation is different to extreme personalisation, and knowing a lot about your customer is not the same as delivering something that will actually engage them,” he says.
So what are some of the best uses of personalisation outside of retail, and what can bricks-and-mortar and pureplay operators alike learn from them?
When you think of the impact that virtual assistants and chatbots will have on customer service, the first thing that comes to mind is unlikely to be empathy.
However, American bank USAA – which works primarily with members of the US military and their families – is developing technology that will interact with its customers through an ingrained understanding of their personal circumstances.
The business is investing in what it calls “digital empathy”, which will essentially allow a customer to have an interaction with an AI-powered device as if it were another person.
The bank’s chatbots will combine data on a customer’s history, such as their last military deployment, with circumstantial triggers such as a baby crying or dog barking in the background of a phone call, as a means of building a rapport with a consumer.
KPMG Nunwood’s chief strategy officer David Conway says: “USAA is a business that trains its staff to acutely understand its customers’ circumstances and then supercharges this with automated machine intelligence, which is a very powerful combination.”
The business has personalised its mobile app to show the tasks a user does most frequently on its homepage.
The app also has a “contact us” button that puts a user straight through to a member of the customer service team who is automatically provided with information on the customer’s query and name before the call is connected, allowing them to greet the user personally and resolve their issue without the consumer needing to explain it.
“When personalisation is done right, it feels invisible. You don’t realise it’s being catered to you, you are just having a customer experience that feels legitimately helpful – that’s when something is genuinely relevant”
David Carr, DigitasLBi
“It’s a business that is constantly learning about who its customer is on an individual level, and what they are likely to be experiencing as a result,” says Conway.
“When you put the two together and throw automated technology into the mix, it has a remarkably high level of predictive power.”
Catering to self-improvers
For many retailers, personalisation focuses on predicting the next purchase a customer is likely to make based on the products they’ve purchased in the past.
But what if retailers could use the knowledge they have on their shoppers to help them accomplish their personal goals?
The BBC is doing just that with the launch of its online programme Cook-Along Kitchen Experience (CAKE), developed by its research and development division in response to the rise in popularity of cookery shows.
The programme customises recipes based on the user’s familiarity with the ingredients used and cooking methods involved, and adapts the pace of instructions to the speed of the person following the recipe.
“Because it supports its user in becoming a better cook in real time, CAKE has the potential to be a phenomenally useful piece of kit,” says Carr.
“When personalisation is done right, it feels invisible. You don’t realise it’s being catered to you, you are just having a customer experience that feels legitimately helpful – that’s when something is genuinely relevant.”
This self-improvement personalisation tool is not just the preserve of a well established business institution like the BBC – fintech start-up Monzo has also gotten in on the action.
The business allows shoppers to transfer money from their bank account onto a pre-paid card, which is linked to a mobile app that tracks your purchases in real time.
Monzo allows users to set their monthly spending targets and will send push notifications of what they have spent in a day or if they are spending cash too quickly.
By creating a service that is genuinely useful, these tools incentivise users to share their data. There is a clear return on investment for the information they divulge, be it in the ability to cook a new dish or put some money into savings at the end of the month.
Remember and remind
Two companies that unearth relevant information for their customers are Netflix and Spotify. So how have these two subscription-based businesses cashed in the money from personalisation?
For Spotify, its algorithm-driven music recommendations – including discovery playlists that expire and are updated on a weekly basis – cater to its users’ tastes while creating a sense of urgency.
As well as its roster of regularly updated playlists, the music subscription business uses its user knowledge to induce nostalgia.
Spotify’s recently introduced Time Capsule playlist compiles songs its users may have listened to in their formative years with an eerie level of accuracy.
Rather than partake in any significant promotion of this new feature, Spotify quietly uploaded it and allowed canny subscribers who spotted the offer to express their delight on social media.
“Spotify’s model has used personalisation to build a behaviour in its customers, who will repeatedly come back to these playlists, and be“Spotify’s model has used personalisation to build a behaviour in its customers, who will repeatedly come back to these playlists, and because it continues to learn over time, it only gets better,” says Carr.
For Netflix, catering its marketing strategy to a user’s tastes has proven a formula for success. The business created different versions of the advert for its latest series of House of Cards, which it showed to users based on their viewing history.
The business also justifies the recommendations it makes based on programmes and films streamed in the past and give a percentile recommendation of how good a fit any given television show is for an individual.
These non-invasive cues based on a user’s past interactions make consumers feel that these subscription-based businesses know them in a way that genuinely improves their customer experience.