How to build brand loyalty in the age of 'hyper personalisation'

Consumers have more power over brands than ever before. Social media gives them the ability to openly scrutinise or share their great experiences directly with a mass audience, while online shopping means brands are in an ongoing battle to cut prices, hold user attention, deliver products quickly and ultimately stay relevant to keep consumers loyal.

Consumers also expect a lot more from brands. We’ve become accustomed to recommendations from companies like Amazon, who have changed consumer expectations by tailoring their offerings, based on previous purchases, to the extent that brands can no longer get away with ignoring online behaviours. However, often these recommendations are based on outdated algorithms and collaborative filtering.

It’s no longer enough for brands to address consumers by their first name in an email on their birthday and think that’s the personalisation box ticked. Hyper personalisation is about using data to react to consumer decisions in real-time, such as notifying them about a discount on shoes as they start their search in your app.

Businesses need to bring loyalty programmes into the digital age or risk losing the consumer base they’ve worked so hard to build.

Getting hyper personal

New data from research firm, YouGov, has found that 48% of loyalty programme subscribers are more loyal to those brands. They also found that 87% of consumers are looking for loyalty programmes that offer them discounts and offers. So why are so many brands failing at this at best - and ignoring it at worst?

The reason is simple: bad data. Traditionally, a brand would profile a consumer using a variety of factors such as age, gender, location and financial status. Take this for example: two men, both born in 1948, self-employed, wealthy, married, have dogs, own a house in London, have children and like fine wine. On paper, these two men are almost identical but in reality these two men are extremely different. This, in fact, is data pertaining to Prince Charles and Ozzy Osbourne. This highlights the main flaw with the data that brands are currently using to ‘get to know’ their audience.

So what other avenues can brands explore? Technology is evolving rapidly, so many brands may not be aware of the golden opportunity presented by advancements in AI (artificial intelligence) and computer vision analysis for mobile devices. The data on our smartphones says everything about who we are. From the places we visit to the photos we take, smartphone data provides more insight about our daily lives and habits than any other data imaginable. With consumer consent, brands can now take advantage of on-device AI, to quickly analyse that data - which includes GPS information, photo galleries, browser history and more - to build a persona for that user.

This first-party collected data is the key to the next generation of hyper-personalised consumer loyalty programmes. For one example among many, on-device AI can analyse a consumer’s entire photo gallery to produce insights about a consumer’s likes and dislikes, their desires and their intentions for the future. It also tells brands about a person’s socioeconomic status and indicates their spending power. This data is gold dust and, in the right hands, can be used to create personalised and relevant discounts and offers, benefiting both the consumer and the brand.

Imagine if you could offer a consumer what they want, need and care about, in real-time. This could be a specific discount at the moment that will be most useful, for example, discounts on home goods when they are about to relocate, or links to cheap train tickets when you know they are planning a trip. For forward-thinking brands that want their loyalty programme to stand out, this is clearly it – by showing your consumers that you really understand them.

Ultimately, this requires a shift in thinking. Brands are often rightly concerned about where the next consumer is coming from. Quarterly profit statements and shareholder scrutiny means brands need to be on the lookout for ways to improve market share. But this should not come at the expense of the existing consumer base. The potential ROI from just increasing sales to current consumers by 8% could be a significant increase in profits for many businesses. And all of this could happen overnight, by simply putting more emphasis on helping current consumers to purchase more of what they want, when they need it.

With the recent announcement that John Lewis’ profits have fallen by 99% in the first six months of 2018, the need for this shift in mindset has hit a critical juncture. Many analysts believed John Lewis to be the bastion of consumer loyalty, now they aren’t so sure. But John Lewis is already leading by example, working with Waitrose to trial combining their loyalty schemes in the hope that existing consumers don’t drift away from the brand. This is exactly the shift in mindset that is needed in today’s digital marketplace.

Metadata and understanding visual information are already the main weapons in the ongoing battle for customer attention. By leveraging offline data from smartphones and combining that with online consumer personas, on-device AI and computer vision analysis can provide brands with the ability to give consumers the experiences and recommendations that are personal, targeted and exactly what they need or desire.

It is this kind of revolutionary AI that will provide businesses with the cutting edge to differentiate themselves from the competition and offer the next generation of loyalty schemes. For anyone looking to knock John Lewis off the top of the retail tree, investing in this technology is paramount.

Interested in hearing leading global brands discuss subjects like this in person?

Find out more about Digital Marketing World Forum (#DMWF) Europe, London, North America, and Singapore.  

Related Stories

Leave a comment

Alternatively

This will only be used to quickly provide signup information and will not allow us to post to your account or appear on your timeline.

obatherbal
17 Oct 2018, 9:59 a.m.

nice

Reply