It wasn’t so long ago (although it seems ages ago) that customers were okay waiting 24-48 hours to hear back from a business when they initiated communication via phone or even email. This wasn’t reserved just for customer service, even an email to sales held little expectation that a response would be immediate.

Reacting or responding to a client request was the way many companies would engage with customers – they were there if customers needed them. It seems almost quaint in its simplicity!

Then some businesses realised that becoming more proactive, especially with customer service related issues, could have material impact on call center volumes and reduce service interruptions due to lack of payment. For example, rather than allowing gym membership renewals to fail because a customer’s credit card expired, smart gym managers ran a search every week for customers with payment methods due to expire in the next 90 days, then sent them a message with a link or phone number to use to update the information. In other words, businesses began to act as if they knew and cared about their customers beyond just the first sale.

However, with the advancements of technology has come an ever-increasing customer expectation. Now we’re in an environment of ‘always on, always available, know me, engage with me in the channel I want’. While it took a while to go from reactive to proactive, we are rapidly approaching customers expecting ‘predictive’. If a customer buys high-end shaving cream, they’re also likely interested in other men’s skin products and perhaps even particular brands of shirts, ties, shoes and watches. If they buy a particular type of camera, they’ll need to find out about protective carry cases, batteries and memory cards. Recommending what a customer may need because of something else they have purchased is now table stakes for many high-performing growth companies.



However, that is only part of the opportunity here. The golden ticket here is working out how a business can surprise and delight its customers by predicting what they might not even know they want or need. That part of it is now relatively simple – if you have the right technology then it’s a matter of using that technology to identify (customer) lookalikes – analysing the behaviour of thousands, or millions, of others who have purchased the same product and finding more like them, either externally or within the existing customer base.

And on the customer service side of the business, technology can be used to predict, for example, when an escalator part might fail, and to route a field service agent with the right part and training to preempt the problem, saving an airport or shopping centre from hours of downtime. It can predict when a service team might be required in a certain area for a telecommunications firm, after a specific type of weather incident. The use-cases are endless when you begin to apply predictive maintenance alongside IoT and Fourth Industrial Revolution technologies.

Satisfy customer expectations, or else

 

As leading consumer businesses are beginning to do predictive customer service well, customers now expect the same from every brand they deal with, whether it’s B2B or B2C (the fine line between the two has almost disappeared, thanks to the fact that the end user is always a person). We consumers have been trained to react a certain way when a brand isn’t predictive, or when our gym membership expires and we haven’t been promoted to renew it. ‘Really? It’s 2019!’, we say. And it’s an interruption in the relationship, prompting consideration of other subscriptions or brands. It’s no longer effortless for the customer to stay where they are, and there’s a good chance that they’ll switch because of it.

I mentioned that being predictive is simple in its concept, but don’t mistake that simplicity for being easy to execute in a consistent and scalable manner. It’s not just about collecting data, or deploying the right technology. While “data is the new oil”, I like to add that if data is the oil, then analytics is the refinery and intelligence is the petrol that will power the business – if you use it.  I’ve seen businesses collect and analyse data, then do nothing differently as a result.

How do you start, or start over, if your business is not managing data as well as it could? First, get a handle on what data you have right now. Where is it? What form is it in? How accurate is it? Do a data stocktake and create an inventory.

Then figure out what data you need right now, based on what is hopefully your new way of thinking around communicating with customers and ‘customer first’, ‘customer centric’, ‘customer success’, etc. The data that you need right now is your starting point – gain permission to use it.

Data: Can it work with privacy and trust?

 

Personalisation and privacy can sometimes appear to be opposing ideas, but actually they can work very comfortably together in the right environment.

Millenials are less likely to share data if they get nothing in return. Our research shows that 79 per cent of customers are willing to share relevant information in exchange for contextualised interactions in which they, as customers, feel as if they are known and understood. And 84 per cent of customers say being treated like a person, not a number, is very important to winning their business.

So communicating the positive effect of data on a customer’s experience is enormously important. If an app requests access to my contacts without telling me how I’ll benefit, then of course I’m less likely to agree. But if I know how my experience with a brand will improve as a result of me sharing my data, I’ll be more inclined to do so.

Retaining that trust depends on using the information shared to truly improve CX, and a decline in trust is directly related to a decline in earnings – so using data well is essential.

Tiffani will be speaking at the Salesforce World Tour Sydney on Wednesday 6 March 2019 in the International Convention Centre. Make sure to register your spot today!