'Successful eCommerce Personalisation: The Experts View', by Rob Jackson, UK MD, Elisa DBI

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If personalisation works so well – why don’t more brands use it effectively?

Personalisation is hot property in digital marketing at the moment. The ability to present users with more relevant experiences in the purchase cycle resonates with advertisers and brands alike. Increasingly competitive landscapes mean it is more important now than ever to get the right message to the right person at the right time.

Despite the apparent opportunity it seems many brands fail to deliver meaningful personalised experiences for their customers. Let’s take Amazon for example; I’ve been shopping with them now for over 14 nears, from which they must have a wealth of purchase data to work with. Last week I bought a pack of Oral B Tooth Brush heads and some tumbler glassware. This week’s personalised email suggested I purchase an Oral B toothbrush and some more tumblers despite common sense dictating I owned both of these products already.

So where are companies going wrong? What is the real opportunity? I spoke with three of the leading technology providers in the personalisation space to learn more about the challenges and opportunities faced by digital marketers looking to succeed with personalisation.

Why do you think so many businesses fail to implement effective personalisation experiences across their content and marketing portfolios?

Ian McCaig, Founder & Marketing Director, QuBit Group:
The simple answer here is lack of high-quality data to begin with. With so many data assets out there, online businesses can struggle to work out what’s relevant and useful for them to tailor their websites to their customers’ needs. Big Data personalisation is a key trend for 2013, but unless the personalised experience has been implemented based on thorough insight, the customer is more likely to leave the web page rather than make a purchase. Therefore, to achieve valuable insight, you need to work from good data to begin with. This allows you to understand what needs to change on the website for a particular audience to improve their experience.

Jamie Brighton, Product Marketing Manager EMEA, Adobe:
Personalisation means a lot of different things to different people. At Adobe, we believe that personalisation spans everything from simple A/B testing of landing pages and the user experience, all the way to an omni-channel approach that takes in on and offline data to speak directly to the customer. Knowing where to start is often a big issue – with so many elements of a site or mobile app that could be tested and optimised, where do you focus your efforts for maximum impact and shortest return on investment? More often than not, internal resistance to change is the biggest initial hurdle, and so being able to build an internal business case for optimisation is often crucial.

Roger Doddy, Director, Peerius:
The key word here is effective. Many retailers think they have personalisation, and they do, but they are stuck in the past, with what we call ‘first-’ and ‘second-generation’ solutions. These outdated solutions recommend products, or deliver experiences, based on ‘community’ insight, slavishly following what customers previously looked at and bought, or what others have bought in similar circumstances. The problem is these solutions are not so effective today, in merchandising and marketing to more sophisticated consumers. Today, effective personalisation means focusing on the individual by examining their behaviour on the site, and deploying content and experiences that reflect that behaviour, and preferences that can be inferred from it. The retailers who can deliver ‘true’, third-generation personalisation are the ones that stand out – and in fact, the results speak for themselves.

What are the key components to a successful personalisation strategy?

Roger:
Best practice personalisation has now gone beyond simple recommendations and community insight. Best practice personalisation uses all available information, drawn from individual user behaviour and operates consistently across all customer touch-points and digital assets.

That is not to say that there is no need for human input. Effective personalisation is not plug and play; it must be tightly integrated with wider marketing campaigns and merchandising priorities, and it must reflect external conditions and events – the weather, micro-trends and so on. That means a really effective personalisation strategy must leave room for expert, human intervention.

Ian:
Without good insights, developing a successful personalisation strategy is difficult. So what constitutes as good data?

1. Measuring visitor behaviour; the who, what, where, and most importantly, the ‘why’ part of the purchase cycle.

2. Covering all bases to ensure a complete understanding of visitor behaviour.

3. Arriving in a common currency; if you’re collecting lots of data, or big data, the task of querying becomes much more straightforward if the data sets are compatible.

4. Structure; this begins with precise categorisation and ends with well-organised storage, again, all in the pursuit of simplified querying and investigation.

5. Create compelling content that is tailored for specific customer segments. This could be a targeted landing page or a web application like a rating and review engine or even just a more targeted message to help the user to convert.

6. Tracking performance is the final step. Ensuring you are delivering an uplift is important, so AB testing and measuring your personalisation with a control group is key.

The end result is for marketers to be able to create websites that are tailored to consumers on the fly, based on real-time analysis of usage habits. It’s our belief that businesses able to rapidly respond to visitor behaviours will create the best online experience, and will earn valuable brand equity with their customer base.

Jamie:
Content, delivery and data are the key things that need to be in place for successful personalisation. Content shapes how we communicate with our customers and needs to be relevant for whatever channel they are looking to engage with us on – web, mobile, social etc. We need to be able to deliver that content in realtime in the right format for the device, often dynamically assembling it at the last millisecond. Data tells us how our content is working, what to test and where to personalise, and also shows us how effective our strategy is.

What considerations should be taken into account when considering user privacy?

Jamie:
Companies that are looking to use customer data, no matter how seemingly trivial that data is, in order to personalise the user experience, should be open and transparent with the customer about what they are intending to use and what the benefit is to the customer. As long as the value exchange is made clear, then most consumers are willing to share enough information for them to receive a better experience, or complete their tasks in the most efficient way possible. It’s been in use for a while now, but I love the bt.com Cookie Settings screen that clearly allows the user to set the level of information they share, how much is shared and for what it will be used.

Roger:
It is very easy to point to regulatory considerations, like the Data Protection Act and the proposed EU privacy regulations, but personalisation data is, or should be, as anonymous as possible, which normally means some form of pseudonymity. In practice, this means Peerius is mindful of its responsibility to deliver not only the best customer experience and great results for retailers, but to also ensure that consumers receive the high level of data protection they have a right to expect.

However, we cannot speak for other providers, particularly those historically operating outside of the UK and the EU – so it is definitely worth considering how their data storage practices, and where they store data, might create privacy risk and regulatory exposures.

Ian:
Online privacy and personalisation is a hot topic and it’s important that companies don’t cross any boundaries. However, receiving feedback from users on why they’ve left a web page is a vital part of the data analysis process, if companies want to improve their online experience. As a result, our tools group consumers together via browser type, number of page clicks, when they abandon their basket and so on. When a webpage senses a potential customer is about to leave, a feedback box pops up, providing them with an opportunity to say exactly why they’re leaving, whilst avoiding the need to ask for personal details.

Which companies do you see delivering a quality personalised experience to their users?

Ian:
We work with a number of companies to help them deliver a high-quality personalised online experience. For example, one of our fashion retailers, Stylistpick, has seen an increase in conversions of 33% across one customer segment. They noticed that users who visited a second category page without putting a product in their basket were less likely than other groups to convert. Furthermore, the analysis revealed that Google Chrome users were the most price-sensitive customer. In order to optimise their website for these different groups, Stylistpick implemented a personalised discount offering 25% off for Chrome users who arrived on a second category page without putting anything in their basket.

Jamie:
More Than Insurance is a great example of a company listening to what their customers are telling them, and then repeating back what they’ve heard, to create a level of reassurance in the brand. By using the breed of pet that someone is trying to insure on the More Than pet insurance product, and repeating this back to them visually during the quote process, they saw a 4% lift in completed policies. Equally, Laithwaite’s wine is remembering customer purchase habits and using this to not only enhance the user experience for loyal customers – leading to a big increase in repeat customer business – but also noting when the user is a first-time visitor and giving a different experience designed to turn them into a customer.

Roger:
The quality of a personalised experience can be measured in only one way – it is effective in driving sales? Based on that parameter, Arcadia Group is a great example of a business applying real quality. It has implanted a single personalisation solution across all its fashion brands, and realised some stunning results. Average order value has increased by 67% and average units per order by 66%. In fact, 7% of Arcadia’s online sales are driven by personalisation alone. Another example is the specialist retailer, Lovehoney. It set out to convert curious browsers into buyers, using some smart and nuanced personalisation. Again, the results speak for themselves. Average order value rose by a massive 74% and average units per order by 43% – what’s more, during A/B testing, revenues jumped by 30%.

Qubit and Elisa DBI are hosting a Personalisation event at Conversion Thursday this week on the Battersea Barge. If you would like to learn more about personalisation, attendance is free. Tickets are still available but limited so grab them while you can.

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