According to Aberdeen, personalised email messages improve click-through rates by an average of 14% and conversions by 10%.
Win more through targeted email and cross-channel campaigns
If data is king and testing is queen, personalisation is the prizewinning prince of digital marketing.
Marketers see an average increase of 20% in sales when using personalised experiences, and personalised emails deliver 6x higher transaction rates, say Monetate and Experian respectively. According to Aberdeen, personalised email messages improve click-through rates by an average of 14% and conversions by 10%.
So how can you leverage the full potential of this engagement power tool? Begin by thinking about what your objectives are around using it and bring it into your processes early in the customer journey. This way, everything can be integrated and aligned with your data and the holistic strategy of your organisation.
“You have to have a business case and understand that right from the start,” says senior consultant Emma Church. “Personalisation comes from the top, feeds the business objectives and increases ROI.”
“Personalisation comes from the top, feeds the business objectives and increases ROI”
Then follow these steps:
1. Look at product, data and segmentation
Let’s begin with the basics – what is it that you want to push to your customers? Look at your data set to see what is popular and break it down by segment. It is futile promoting a credit card for high earners to every 22-year-old, for example. Segmented and targeted emails generate 58% of all revenue, according to the Direct Marketing Association, while Campaign Monitor reports that marketers have noted a 760% increase in revenue from segmented campaigns.
Data must be clean to ensure a flawless customer experience. Keep it in the right place and build a data lake or an infrastructure to process and leverage it.
“Remember, testing is queen. Before you send out any communications, make sure all your hard work is worth it”
2. Going deeper using data science
To take things up a level, data can be predictive too. “Data science can be used to know about a customer’s behaviour and also that people with similar profiles like certain things,” says Emma. “You can recommend products and experiences based on this to make it as personalised as possible. Data scientists can go even deeper – uncovering things you didn’t know before about your data.”
Deeper levels can include creating automatic triggers. An algorithm with 90% accuracy can tell you a customer is likely to make a purchase in the next three months. Another algorithm could tell you that, based on previous purchases, she will buy a particular product. You can then send a recommendation.
Data science consultant Andrea Camacho says: “If John Smith is going to buy a car in three months from now, you can capture related content and send it to him by email, SMS and other banners. If he looks on Amazon he will find it in every other website he navigates, on banners saying ‘we know which product you are interested in, do you want to buy it now?’.”
“You can also use data to see when is the best time of day to send an email to a particular individual. You can see their location and what the weather is like – if it’s cold or raining suggest a hot chocolate drink in front of their fireplace, if it’s warm prompt them to visit a store they are near to.”
Decide your parameters
Ask yourself: what are you trying to achieve, how much time do you have and what can you realistically do within your budget? It could be as little as putting the recipient’s name in the subject line and the body copy. According to research by Campaign Monitor, emails with personalised subject lines are 26% more likely to be opened.
If you have wider resources and want to go a little further, look at adding in personalised gifs of images. For example, when Burberry launched its new fragrance ‘Mr Burberry’, every male email recipient received a personalised message – with his own initials on a mocked up aftershave bottle in the hero image of the email. If you only have one week, take a very direct approach. This could mean sending just one communication with easy to implement personalisation techniques such as including a customer’s name, favourite store, recently bought product and geographical region.
3. Integrate cross-channel interactivity from beginning to end
Put your customer first and think from the beginning: how do they want to interact with your brand and buy your products or services? If your internal marketing teams work in silos, de-silo them. Adopt a collaborative approach instead.
“Typically, the email marketing team will just send their emails and the digital team will create their online banners, for example,” says Profusion client manager Thomas Silk. “As teams, you can each have brilliant ideas but you need to come together and communicate with each other internally if you want to create an integrated, smooth-flowing journey.
“Email could be a starting point, then link this up with online banners or schedule the email to go out after the TV ad goes live, for example. This way, customers are going from one stage to the next.”
If you want to increase conversions and engagement with the customer, work closely between teams and design all messaging and tools together. Remember to make it easy for the customer to go straight to purchase, with opportunities for you to up-sell along the way.
Continuity and ease of access from a customer point of view is integral to completing the purchase. For example, if you get a personalised email but it’s not a one-click-to-basket type of journey, you might not buy the product on the day you get the email. It might send you to the main site so you have to find the product again and might see something else and leave. As a marketer, that product was the hook to get you to revisit the site, but you don’t want me to drop off the page.
4. Test everything
Remember, testing is queen. Before you send out any communications, make sure all your hard work is worth it by ensuring you or your eCRM provider carries out the correct checks.
“Never stop testing,” says Emma. “Every test provides new insights and the list of items you can test is huge. Always consider the things that influence a test, also – such as seasonal effects. Test one thing at a time so you don’t confuse results, unless you choose the ‘experimental design’ route which data scientists use to see the effects of testing everything at once.”
“By constantly looking to improve, you can really enhance personalisation and the overall customer journey”
Emma adds: “It’s important to test a personalised message against a generic one, to see the difference in engagement measures and prove the benefits of adding those personalised touches.”
If you’re sending a campaign to 100 people on Tuesday, pre-test by sending version A to 10 people and version B to 10 people on Monday. Then track engagement on each to see what works before tweaking and sending out the campaign to the rest of the sample.
Remember to use a control group. No matter what you are testing – from a simple call to action placement test to a full multi-channel effectiveness programme – a control is an absolute must if you want to effectively measure the results.
5. Continuously improve
So your personalisation tricks have pumped up the number of opens, clicks and dwell times. You’ve cut complaints, opt-outs, and end-to-end junk and won more website visits and purchases. Congratulations. Now it’s time to look at what you could do next time to make it even better and more personalised.
“By constantly looking to improve, you can really enhance personalisation and the overall customer journey,” says Thomas. “Look at what was effective or memorable in the message and across the entire customer experience. Follow up with another message according to which links were clicked on. If someone clicks on the first link, send them message A, if they click on the second link use message B. If they click on more than one link, go with message A. If you pre-tested versions 1 and 2 last time, try testing 2 and 3 next time.
Depending on the product and timescale, have a four-week lead time instead of two weeks if possible. The more time you have to plan and investigate ways of personalising the journey, the better.
From a brand recall perspective, think about whether customers remember getting the personalised message. Did it drive an action such as filling in a survey about how useful they found an email? You can then integrate that data back in to support future personalisation opportunities. Jazzy personalisation might get better open rates but are you getting better sales? Are customers noticing and are they differentiating you from the rest of the market?
The objective of using a personalisation tool might not be to sell a particular product. You might wish to take someone to a landing page and capture more data there that will then trigger your next action. For example, discover when their existing product or service expires. Record this information and use it to send a timely and relevant communication that will inspire a more positive action in the future.
6. Replicate and automate
“Once you have made your improvements, automate everything with data science,” says Andrea. “Get the learnings that worked or didn’t work. Then replicate, automate, replicate, automate …”
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