Held in Farringdon on the 30th September, the latest Together We’re Better event looked at personalisation.
Personalisation is a bit of a buzzword at the moment. Our speakers were keen to break down what personalisation is, and how it can be easily incorporated into your content strategy.
Presenters were David de la Peña, Technical Strategist and Ben Jackson, Content, Community and Social Media Strategist. The presentation to accompany this blog can be found on Slideshare.
Bill’s improved experience
David began the session with a clip from Groundhog Day. In the film, Bill Murray’s character replays a day over and over again. With each replaying he learns more about the people and situations around him and is therefore able to better react to them. What he learns each day improves the experience for both him and those around him.
The Age of the Customer
A Forrester report “Competitive Strategy in The Age of the Customer” (2013) maps out the key economic phases from the past 100 years. Starting with the Age of Manufacturing, moving through the Age of Distribution and then the Age of Information. Now, Forrester claim we are entering the Age of the Customer.
What is personalisation?
It is about getting the right content to the right people at the right time. This means better results for brands and organisations - you’re getting more targeted advertising and content out. But, it also means an improved experience for consumers as it delivers more relevant information.
Amazon and Spotify both offer fantastic examples of personalised content. Amazon’s recommended products are based on previously bought items. So, if you’ve bought a pack of nappies recently, Amazon may assume you’re a new parent and recommend baby baths and bottles. Equally, Spotify recommends similar artists and genres to those you’ve been listening to. Both provide a better experience for the user; providing genuinely useful recommendations. These recommendations also fuel further engagement with the organisation, either buying more products or connecting more with the service offering.
Another example is Google Now. Automatically installed on android phones, Google Now dips into your email and works out where home is, finds news and products it thinks you might like and even notes which car park you’ve left your car in.
Creepy or cool?
Running through a few further examples, we can see some ways in which organisations have used data in really cool ways. We can also see some examples which are a little creepy...
Take Target as an example. The American retailer monitors closely what shoppers buy. This data allowed the store to assign shoppers a “pregnancy prediction” score. Target then began sending out coupons for baby items to customers that were flagged up as likely-pregnant according to this score.
One angry father got a little peeved when he discovered his teenage daughter receiving baby coupons and went to his nearest Target store to complain. Of course, they knew nothing about it but when the store manager called a few days later to apologise again, the father was the one apologising as it turns out his daughter was indeed pregnant. Target worked out a young girl was expecting before her own father did.
Creepy… yes. But quite a fascinating use of data to drive sales. Target have since dialed this back, still using the pregnancy score but mixing the baby products into a booklet that appears to be a random selection of coupons. They found that as long as the woman thinks she hasn’t been spied on, she’ll use the coupons. Nectar do something similar. Have you ever wondered why your vouchers are often for the items you regularly buy? Not a coincidence.
As with a lot of charities, Marie Curie email supporters asking them to donate. The charity found however that if people were opening the email on mobile, and following the route to donate, there was a huge drop off. So, the charity embedded a small piece of code that started recognising when someone was opening an email on a mobile device. Then when they clicked to donate, instead of the usual donation experience, they were presented with an easy SMS option. Donations from mobile dramatically increased.
In other retail examples, LK Bennett realised that high-value customers (that is people who have a high retail value of good in their basket) who had left the site, but not yet purchased could be encouraged to buy those items when they returned to the site by offering free delivery. They also recognised that UK buyers were highly interested in the returns policy. They added a little tracker that noted when a visitor was from the UK and added a clear bubble of text outlining how items can be returned. Sales increased.
Obviously data is a huge consideration in any marketing strategy. How this data is looked at and interpreted is key to successful personalisation. But what kind of data are we talking about?
- Third party data - wholesale, bought in data lists
- Personal data - built from information added to a profile
- Behavioural data - tracks clicks and content
- Contextual data - time of day, weather
How to get started with personalisation
While it may be tempting to jump right in, a considered approach, taking small steps is best.
- Easier to get budget sign-off
- Easier to get internal buy-in/support
- Easier to manage
- Easier to track and measure
- Easier to prove success
- Easier to manage data
- Easier to avoid embarrassment and pitfalls.
What could you try?
Race for Life are doing brilliant things with video personalisation at the moment. They film a video, leave certain aspects of it blank and then populate with personalised information drawn from a supporter database. For example, a video might greet the user with their name and then ask them if they can beat last year’s race time of 47 minutes.
Sending your email recipients more relevant email content. For example, if you know a segment of your users are massive penguin fans, you could send them facts and rich content about penguins. Some A/B testing here would reveal whether they react more favourably to the tailored content, and it drives engagement/donations/traffic (whatever your metric for success is).
This could involve basic tactics such as targeted ad campaigns, or more creative experiments such as inviting supporters to submit a profile picture and then using a collection of pictures to create a large scale output - for example a projection.
Top survival tips
- Don’t try too much too soon
- Ring-fence some budget to test a small personalisation tactic
- Be clear on what you want to learn and how you are going to measure and benchmark
- Be willing to test and learn