Personalisation in marketing is key to getting your message through the clutter. The massive billboards along the highway and populating cities are owned by major brands whose business is based on volume. Your business, while growing, is still making personal connections. You know your customers.
As you grow, however, you’re finding it harder to make those connections. It’s the nature of growth. You don’t have to sacrifice the personal touch that has given your business its reputation.
Automation is creeping in to a variety of marketing functions, however it can be overwhelming and off-putting. When I was shopping for a new vacuum cleaner, I did a few searches on it. And, from there, I couldn’t go to any website without seeing a barrage of ads for the products I’d been looking at. It was almost creepy, how I was being tracked. And I know I’m not alone in my assessment. It’s gotten so bad that users are turning to ad-blocking and registry-protection programs like Ghostry to keep their browsing history somewhat secret.
Personalising your message can lift sales by 10% or more. Being intrusive, however, can turn off your customers, undermining your marketing intentions. The marketing industry has been spending decades promising a scaled, personalised experience it has largely been an intrusive deluge rather than a seamless reminder helping businesses close sales.
Existing remarketing is the same as having a staffer follow around anyone who has ever been to your store and throwing flyers at them whenever they walk near another. What can we do? Scrap your existing processes and better use analytics.
You need to be able to test your processes, learn from successes and challenges, and adapt to the needs of the consumer. Many marketing agencies will encourage you to A/B test, and they’re right on the concept if not the execution. It’s more than version testing, it’s about finding different avenues to engage your customer.
Data is the key, but finding which data matters is where you get to version testing. You know your customers habits on your sites. Now learn how that collates to your marketing spend. It’s easier said than done, of course, but you need to follow the bread crumbs. If customers generally do A, then B, then C, you need to encourage people to follow that path. When A happens, trigger personalised, automated messaging that encourages a prospective customer to take the next step.
Collate the data from your first-party sources to help score the probability of how a customer type responds to different, specific content. If you know that people who buy X respond positively to an email and negatively to a banner ad, then avoid the later. It’s about assisting, or expediting, the decision making process.
Standard data models can put out offers—you’ve been on the site for 5 minutes looking at 3 different products, so here’s a coupon to close—but you should be enabling two-way communication. What’s great, in theory, about going in to a store is that there are people with more experience to discuss pros and cons of differing products. We also want to be able to gauge interest so you’re not wasting future efforts for a disinterested party.
The final is specific content, offers, or personalised ads to help get a person across the goal line. If you know that BMW drivers in London who like going to economical restaurants tend to prefer luxury services like cable bundled to present the illusion of value, then you need to get them a personalised offer. The information is out there and available to a team that’s willing to put the processes in place. But it needs to be triggered by optimal conditions to ensure that you’re not wasting effort or, worse, turning off a potential customer.
To do this, you’re going to need systems that play well with other systems. API that links back to social networks where your customers are volunteering heaps of information. You need to be cycling information in real-time to make the most of triggers, or even get leads to your sales team when a prospect is at their most-likely to close.
It’s ultimately about building a deep, meaningful relationship with your customers and your brand so that you’re able to make the most of your data in support of your customer’s needs.
Are you using API? Making the most of data? What are you doing differently? Sound off in the comments below.