Kate Elizabeth — 23 January 2019
A recent email from my favourite acrylic artist paint company, suggesting that because I had purchased several shades of pink from their range, I might also be interested in their purple-based colours, is a good example of personalisation. The recognition of a past purchase and linking the product selection to that, rather than a generic push of any colour, was
Personalisation isn't just about adding merge tags - personalisation is using data at scale to increase the relevancy of the message and the brand to the person and situation.
With the amount of data available to marketers through CRM, tracking tools, behavioural and intent analytics, it is possible to build journeys and experiences where your customers feel valued and appreciated, rather than a cog in the machine. It also helps you to be more efficient in marketing production and drive better results.
Evergage, a provider of 1:1 personalisation through their customer data platform, share these key statistics around the benefits of personalisation:
Statista published study results for open rates: the open rate for personalised emails was 18.8% as opposed to those without personalisation (13.1%).
Marketers can see an average 20% increase in sales when using a personalised web experience according to Econsultancy and Monetate.
Adage's research highlights 33% of marketers identified personalisation as one capability that will be most important to marketing success in the future
Marketers clearly understand personalisation makes a difference, but with less than 40% of them using it to optimise the customer journey, let's explore why.
Before we can personalise, we need to answer several key questions:
Once you have identified what success looks like, and the levers you can move to achieve this success, you need to find how you can influence these levers. What data do you already have (even siloed) that provides insights into customer behaviour and can be tied to a customer segment or customer record?
Most enterprise-level organisations have an excess of data and marketers have access to additional sets through tracking mechanisms. Use your goals to inform the data sources and build profiles from this data to identify the personalisation attributes.
Create segments from your data by identifying personas like the categories of buyers. Are they B2B or B2C? Is their role important? What is the purpose of their purchase? For example, you might have buyers who buy for themselves and another group who are buying your product as a gift. Identify common behavioural characteristics like when they are engaging with your content or purchasing. Are they visiting your site multiple times before purchase or do they purchase as a first-time visitor?
Map the customer journey, identifying the touchpoints, the data exchange and tracking that happens (or can happen with a few more tracking mechanisms) to identify microsegments. For example, not everyone who buys a present is the same persona or segment. What is their age? Gender? Did they select an item aimed at a child or an adult? You might end up with a microsegment of women buying for kids under 8.
Where does the value lie in activating these microsegments for both the customer and the company? How can you ensure this microsegment buys more frequently with a larger cart size?
Perhaps you identified a microsegment from your data that a particular group of people was over-indexing for returns. What data do you have available to personalise marketing and communications to reduce their unsuccessful returns?
Once you start data mining and you realise exactly how small your microsegments can be (even true 1:1) you need to sense check and ask yourself how personalised is too personalised? Just because you can find the data, doesn't mean you should use it - with incredible data sets comes incredible responsibility.
Customers are usually happy to receive personalised content because it means a better experience for them, but that satisfaction is based around data they know they have formally supplied to you rather than harvested data. We talk a lot about permission-based marketing and with GDPR there are now overt approvals for cookies on websites - these are the visible signs of permission-based marketing.
More critical than permission though, is trust. Personalisation is appropriate where there is trust between the consumer and the provider. If I trust a business, I am happy for them to use data to make my experience better. I trust them to use signals and create a response in a timely and relevant way - something I do will trigger a response from them to make my path to purchase better.
Personalised content isn't merely a merge tag with my name. True personalisation needs a library of trigger messages used in response to my actions and signals.
The easiest is tokenised copy - copy explicitly produced for a segment or microsegment - and inserted into a campaign. For example, in an email about the types of courses you offer, a prospective student should receive tokenised content based on the course category and even the course, as well as information about their local campus and local events. You can build a generic email, but if you are trying to move this person from interest to enrolment, selling them on the actual course and location will be more effective.
Additionally, offers, recommendations and images can all be personalised to segment and microsegment. A personalised image at the top of an eDM or landing page will instantly make your reader feel like they belong, and with a personalised CTA will encourage the outcome you want.
Without automation, this is an incredible amount of work. You could be writing copy and producing offers, images and CTA for at least 10-20 microsegments for each campaign.
Platforms that automate the production of the right dynamic content to increase engagement are the right mix in your martech stack. You might use your CRM to inform segmentation, pull the right images from your DAM, use brand automation to personalise the images and content for the send, send out emails through your marketing automation platform directing them to a personalised landing page with the right product, offer, recommendations and call to action. It seems a lot, but with the proper infrastructure, your marketing becomes intelligent and delightful.
Start small with only one or two segments, build attributable results and then expand to drive even better results.
And, of course, make sure your martech stack supports your vision!