In the words of Malcolm Gladwell, marketers in 2020 have finally reached the 'tipping point' where scalable hyper-personalization of marketing activities is not only possible, but is rapidly becoming a requirement in order to stay up with evolving consumer trends.
The shift to more towards personalized, targeted shopping experiences is largely due to the advancements in marketing technology, with elements of machine learning, artificial intelligence and biometric identification all becoming more integrated with one another in order to deliver customized promotional opportunities.
An example of this can be found at the Westfield shopping complex in Shepherd's Bush, London - the complex now has cameras in and around the mall which use facial recognition technology to determine the age, sex, and even the mood of the shoppers as they move through the buildings. Based on what the system learns, it can then display different ads on the various digital billboards around the mall in order to maximize consumer response.
In today's digital era, with the advent of such engagement technologies, we are now at a stage where account-based marketing (ABM) and personalization have become more practical and scalable than ever before. With automation and machine learning tools working in tandem, even a small company can run a comprehensive ABM operation, serving the largest possible clients.
As a digital B2B and B2C marketer, I find this very interesting, and ave been pondering how these same types of technologies and ideas can be used to hyper-personalize digital marketing communications using the combination of internet and mobile technologies.
For the past few years I’ve been entrenched in personalized email campaigns, cart abandonment email programs, Facebook custom audience ads, and other forms of personalized marketing strategies, but so many brands are running these same campaigns that they're beginning to lose their luster.
Think about the recommendation engines that both Amazon and Netflix have built - these engines work so well that they've catapulted these companies ahead of the rest, because of the way in which they're able to personalize your experience so well when you use these platforms. They know almost exactly what I want to buy or watch next, and can be so accurate that, at times, it feels like they're reading my mind. That’s the type of hyper-personalized marketing that all companies need to aspire to, in some way.
Many companies are, indeed, improving their efforts on this front. A recent Gartner study revealed that companies which are investing in online personalization technology are outselling their counterparts by approximately 30%.
The buzzword for 2020 should be 'hyper-personalization' - the harnessing of all forms of data being used in unison across all marketing channels and customer journey stages. Embracing this approach is going to move customers from top of funnel awareness to post-purchase happiness in record time through higher and more effective engagement at every stage.
Engagio has put together a spectrum of content that marketers currently create, and now, we need to move away from the far-right of the spectrum and towards the far-left.
So what's the recipe that B2B or B2C digital marketers need to follow to enable hyper-personalization?
There are three main ingredients to consider:
- Engagement - Engaging customers with hyper-personalized campaigns which customize their experience with your brand or organization. According to recent findings by the Epsilon Group, 80% of consumers are more likely to make a purchase when the brand offers a personalized experience. In this qualitative study, one of the respondents reported hyper-personalized campaigns drove 3-4x more engagement with the brand. A B2B respondent reported that full-funnel personalization has doubled its webinar and event registrations. The key here lies in collecting and analyzing consumer data at every turn, and investing the time and effort to understand the key trends.
- Relevance - This is the ingredient that B2B and B2C marketers need to borrow from Netflix and Amazon - it requires truly getting the right message to the right person at the right time, all the time. Many have spoken about this in the past, but we finally have the tools and knowledge available to do it properly, by using richer behavioral data and intent data to create messaging that hits each individual’s personal needs and pain points.
- Trust - If the first two ingredients are added correctly, the third will naturally follow - trust. With so much competition in the online space, customers are going to choose the one that they trust the most - which is why reviews are now so important in every aspect of our process. Aside from customer reviews, good educational content is a prerequisite - companies need to invest in an education team that puts out how-to’s, instructionals and thought-leadership content, especially in video form. This type of content needs to be delivered to the customer based on their specific needs, intent, and funnel stage.
The key to making this recipe work is taking a data-driven approach that's personalized for each account and each person at every touchpoint along the buyer’s journey.
If executed properly, it will result in higher engagement, more customers, a larger pipeline, and larger account wins.
Let’s further define some of the terminologies we’ve used, so that you can walk away from this post with more than a conceptual approach to the process.
- Customer Content Audit - Re-evaluate all of your target customers and their needs at every stage of the purchase funnel. Evaluate all of your current content and tag it by the customer persona and funnel stage. Revise any content that will better suit each persona’s need at each funnel stage. Fill in the gaps by creating new content or identifying influencers that you can partner with to create new content for each persona designed to engage them at their current funnel stage and move them along to the next stage of the journey.
- Intent Data - This type of data can be collected in a couple of different methods: First-party intent data references how accounts interact with you on your properties while Third-party intent data uses the content people are reading on third-party sites to identify which accounts might be actively researching particular solutions.
- Behavioral Insights - Intelligence such as sales profiles that are rich in data on target prospective customers and accounts, primarily using manual research methods.
Again, the buzzword for all brands in 2020 should be 'hyper-personalization'. The closer you're able to get to this, the better you'll be able to serve evolving customer desires.