Exploring real-time data and improving consumer trust

A recent article in Raconteur’s report on the “The Future Customer” raised some pertinent points about the relationship between trust, transparency and real-time insights. While customer data protection sites, like DuckDuckGo, offer consumers extra privacy and encryption, they pose a challenge for brands, who are left to work out how they can develop a deeper understanding of their customers in order to build trusted transactions with them over their data.

DuckDuckGo’s anti-Google positioning and non-data gathering stance sets them apart and they are very honest about how they make money. How successful it is remains to be seen, but if it only provides an alternative for people worried about the use of personal data online then that is a good thing.

However, this then puts the onus back on brands to gather and use the data entrusted to them to build better engagement with the end consumer. Again, this is a good thing: for far too long, it has felt that we are being conned into clicking ‘accept cookies’, but brands need to be clearer and more responsible as to why.

Personalisation and trust

Personalisation is vital in increasing trust between brand and consumer. Why would you trust a company with your data if they cannot demonstrate the ability to use that data well? To be honest, personalisation should be a basic hygiene factor in customer engagement now. And that means not just knowing a name and salutation but using the data you hold. This week I have been asked to take part in an online survey three times, despite the fact that when I applied the first time, my occupation apparently disqualified me. That’s just terrible and it shouldn’t happen anymore.

If your brand trades on sensitive dates or information then you need to think about how you gather that data and use it (and secure the trust to do so at the same time). That’s quite different to using customer lifestyle and interests to build a relationship and hopefully engender trust, which is more about ensuring that the engagement is relevant and helpful and therefore will increase a response (which one assumes builds trust).

There are literally hundreds, if not thousands, of examples where businesses lose data or are breached in some way. While these are awful, they are not the biggest issue for most consumers. For most of us, it is the little things that happen every day that are annoying – I buy some clothes from a retailer and they send me an email with the same shirt the next day; Netflix reminds me to finish a series I started last night; Amazon tries to sell me children’s books because I bought one for my nephew. These smaller “breaches” of trust where I have shared personal data, transactions and permission, are worse than someone losing 4m customer records.

Data, AI and consumer trust

Data is almost certainly critical in gaining consumer trust. AI probably isn’t, but it can be helpful in a few ways: assessing what data is relevant and therefore should be requested; managing customer service to encourage ongoing engagement; learning about what information creates a reaction to an ad or a message and is therefore valuable. As with most things, AI is an addition to helping make something better: very rarely is it the solution in itself.

Different generations have different attitudes to trust and security. The younger people are, the less protective of their data they generally are. What could be interesting here is how the older generations’ attitudes will change post-Covid.

Right time vs. real-time data

Real time is great – but only if your brand is real time. If it isn’t, then there’s not so much of a need for it. Perhaps the correct term should be ‘right time’. For example, an online retail client, where there is ongoing interaction, probably needs to react in real time.

The challenge here is often how you nuance the message based on the fast data (what is being browsed now) and the slow data (age, income, hobbies, interests). When should one supersede the other? When is what I browse more important than who I am? For other sectors, industries or companies, would real time make a massive difference? For example, a charity with very little online presence can easily live with updating all data every day and using that data, static as it is, for the full day.

Our top tips for brands looking to embrace real-time data and build consumer trust are:

1. Decide what data is needed in real time v right time.

2. Agree what data really makes a difference (everybody assumes they need much more data than they really do).

3. Make sure that the data you gather is used, and can be used, in your engagement with your customers (so much data sits in systems and never gets used at all).

Don’t forget that a lot of the data that is relevant already exists: not everything needs to be asked for. Sometimes it is better to ask for less and add more from other places (third parties for example).

Take the bespoke approach

There is no question that there is a war at play on data and consumer trust: the balance of what people think they need to hold against the ethics of asking for, storing and using consumers’ personal data. However, the end game for this has to be bespoke for each individual and brand. What I will share with Amazon versus what I will share with Tesco is going to be very different between me and those brands, and between me and any other person.

This is where AI can help hugely: by creating that measurement of trust between a brand and a customer and then setting the bar on how far to ‘stretch’ that trust. The idea of me having one pot of data I am willing to share with brands has been around for ages but I am not entirely convinced that is the future as my pot will vary by brand. The future will be in helping brands assess who they can have a relationship with that is deep and data driven against those who are happy just to transact.