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How technology is fuelling a more personalised customer experience

(Image credit: Image Credit: M247)

•  ‘Customer experience’ has become a buzzword amongst technology companies; what does this mean to you?

Customer experience includes the entire customer journey; it’s a holistic experience. When the intent is understood at each step in the journey, companies can ensure they’re delivering the best experience possible to match that intent.  It should address pre-sale, during the sales process and after the sale. It’s the experience consumers have engaging with your product or service and why they are interacting with you.

•  How can businesses harness technology to remain competitive against the likes of Amazon?

One of Amazon’s keys to success is its customer centricity, but their massive size makes it harder for them to deliver personalised and bespoke experiences to their customers. To compete, companies can better leverage their data to deliver unique personalised experiences. No company is going to be competitive with everything Amazon offers. The right approach is to be strategic, and use data assets and innovative approaches to customer experience that is clearly differentiated in a specific way.

•  What are the most prominent trends you’re seeing in the market?

I’m seeing three trends that everyone should have a strategy for:

1) Combining proprietary/owned data with third-party data: Brands must leverage the wealth of data they have about their customers to deliver better experiences and combine it with other types of data to make sure it’s comprehensive and relevant (e.g. behavioural).

2) Privacy and GDPR: Customer data conversations evoke a natural concern about privacy. It’s imperative for companies to work with vendors that are compliant and have a solid approach to privacy and GDPR. It’s also critical they have their own internal governance so they can hold their vendors accountable. It’s a two-way street. 

3) Programmatic advertising has reached an inflection point. It’s the standard way companies buy and sell digital advertising. However, there’s a broken connection between advertising to direct consumers and the on-site consumer experience. Companies should ensure they deliver a holistic customer journey so they can programmatically deliver from pre-click to post-click. The deeper a targeted, personalised connection can go, the higher the return on the customer.

•  What are the most prominent challenges for online businesses?

The online environment is extremely competitive, and brands need to constantly evolve to stay relevant. Companies should look at their customer data to optimise consumer experiences and inform their product direction. It’s all about delivering the best products and services to your customers, and customer insights provide the path forward.

•  What are the key considerations when using customer data to serve personalised content?

Firstly, to provide a consistent customer experience it’s critical to have data governance across channels. Shoppers expect the experience to be the same wherever they interact with the brand. Brands can get a full picture of their customers from data across in-store, online and mobile.

However bringing this data together is challenging, teams are often siloed. It’s important to not only think cross-functionally, but act that way. Companies should put a holistic process in place so teams plan customer-first instead of channel-first to deliver the best experiences. It’s intuitive to be customer first, but many companies do not do it in practice.

•  Can Artificial Intelligence help to instil customer loyalty?

Companies grapple with a mountain of data on their current customers. It’s difficult for them to parse through the database to understand key factors that influence lifetime value. However, AI tackles big data and provides insights and trends across the spectrum making data easier to understand.

One example is lifetime customer value. AI can look at key factors that influence LTV to better leverage the right experience to customers to move them to the next step based on deep learning. The technology can then also deliver personalisation, prediction, and many insights that marketers would otherwise never get from the data they amass.

•  Are you able to give some examples of brands or retailers doing this well?

Travelodge is a great example. We worked with the British hotel brand to help them understand what metrics to optimise their customer communications against.

Travelodge ran server-side tests, which streamlines the testing process while significantly reducing costs. Server-side tests work in reverse of most tests. Travelodge uses technology to pull insights from a wide range of data, and then once it finds the winning variant Travelodge can put it live on the site almost immediately for improved relevance. We used personalisation to launch over 30 tests, and were able to implement new tests six times faster and at significantly lower costs than Travelodge had seen previously.

Similarly, Jojo Maman Bebe uses personalisation to test messaging for marketing and uses the insights to make tweaks to content quickly in order to improve relevance. Lots of potential customers who have never shopped with Jojo Maman Bebe before search for terms like “maternity wear”, so the company tried offering different incentives off the first shop for these visitors. It was a simple but effective strategy. The brand immediately saw a 9 per cent uplift in new visitor conversion and now all new visitors receive an incentive.

The company also tested messaging for Christmas, testing different categories of products in both large and small sections of the site. Not only did they see a 20 per cent uplift in conversion, but they also gained useful customer insights that will inform decision making in future campaigns.

The UK grocer Waitrose is famous for their personal and immersive in-store experience. Personalisation helps them bring that individualisation to their online customers too.

The team set up an initial test on the recipe page to see whether AI could help drive engagement by selecting optimal content for each visitor. The experience was targeted to the entire audience using default context and additional CRM data, with a goal metric of driving clicks. They saw results right away: personalisation drove a lift of 6.21 per cent, with 98.6 per cent certainty that the personalised content was performing better than a control group that had received random recipe assignment.

Once the initial results had given them confidence, the team elected to move the experience to the homepage in order to drive click-throughs to the recipe page. Engagement exploded. When exposed to the heavy traffic of the homepage, the recipes experience saw a lift of 66.8 per cent, with 99.9 per cent certainty that the output from the personalisation was better than random assignment.

Lisa Kalscheur, Monetate