Are people becoming harder to satisfy? Yes. The likes of Amazon and Apple have set new standards in customer experiences that we expect other businesses to match. But there are other factors, too. The cost-of-living crisis has made all of us a lot more critical. According to the Institute of Customer Service, customer satisfaction in the UK has fallen to its lowest level since 2010.
In this blog, we’ll explain why personalising customer experiences can boost customer satisfaction, and why we believe leveraging data, and applying analytical techniques, is the mechanism for achieving this. We’ll show how you can kick-start your personalisation strategy today using the data already at your disposal and build from there.
Why customer satisfaction and personalised experiences are critical
Customer satisfaction is critical for long-term business success. It often correlates with higher revenues and market share. There are many ways to increase satisfaction levels, but one of the most effective is improving the customer experience.
A better experience drives customer loyalty and retention, reducing churn and increasing customer lifetime value. It directly impacts perception and encourages repeat business. And it converts customers into brand advocates, driving sales through positive word of mouth.
Particularly in saturated markets, where competition is high and growth increasingly difficult, customer experience can make all the difference. It sets companies apart, meeting a need that many businesses don’t seem to be fulfilling. A survey in the US found that 81% of customers prefer companies that offer a personalised experience. Plus, 70% said it was important for personnel to know their past purchases and interactions.
How data fuels customer personalisation
Personalisation starts with data. It helps businesses understand customer preferences and behaviours. Data can show everything from gender to preferred touchpoints, purchase histories, and brand perceptions. With these insights, companies can tailor their interactions and offerings to customers’ requirements.
Multiple types of data are available. All of them are useful in personalising customer experiences; however, it doesn’t matter if you don’t have access to all of them. The thing to focus on is using all the available information and then devising a plan to collect the data you don’t have and then integrating that with your existing data.
Here’s a list of the kinds of data you want to collect:
- Primary data – You collect this from your website and apps. Primary data covers click patterns, browsing history, search records, reviews, and user preferences. It will help you understand individual user behaviours and preferences.
- Survey data – To provide a more nuanced understanding of your customer base, you should conduct customer feedback surveys, preferences surveys, net promoter score surveys, and customer satisfaction surveys.
- Third-party data – This covers areas like web scraping, which we discussed in a previous blog. It also includes macro data to better understand the world and insights from data brokers or aggregators, which sell data to help you better understand your target audience. We can also add data clean rooms, which are secure environments where brands, publishers, and advertisers can share and analyse their first-party data. Plus, there are walled gardens, such as Google’s Ads Data Hub, which provide detailed insights into user behaviour, preferences, and demographics.
- Historical sales data – Using sales data to support personalisation is self-explanatory. It’s an excellent source for understanding a customer’s preferences and buying patterns, and it can help identify upsell and cross-sell opportunities.
- CRM data – These systems are designed to support personalisation and are a great tool for tailoring customer interactions. CRMs record and manage all customer-interaction data, creating a unified customer profile. You can then interrogate that profile to help personalise customer communications.
- Social media engagement data – Using social media data, you can learn about customers’ preferences and interests. Many companies use it to segment their audiences based on commonalities such as demographics and behaviours.
Turning data into insights to guide your customer experience strategy
Get to work with the primary data at your disposal. Start measuring and tracking how customers are interacting with your website and apps. Conduct customer journey analysis to expose the cause-and-effect relationship between touchpoints and marketing channels. It’ll give you an immediate understanding of how different channels work together to create customer behaviour.
Here are some of the many techniques for extracting the goodness from your data for personalisation. Such as:
- Heatmapping – These visually represent website behaviour through colour-coded overlays. You’ll see, for example, the areas of your website that draw your customers’ attention and where they may be searching for information, giving you insights to improve signposting.
- Behavioural analysis – It enables you to examine how, when, and why customers engage your company through purchasing habits, brand interactions and product usage. It’s a great aid for customer profiling and segmentation.
- Conversion rate optimisation (CRO) & funnel analysis – CRO is the systematic process of increasing the number of website visitors that perform a desired action. Testing and optimising webpages allows you to find the right level of personalisation to boost conversion rates. Likewise, funnel analysis, which identifies critical events along the customer journey, will help identify those points where personalisation will have the greater impact.
- A/B and multi-variant testing – Using A/B and multi-variant testing, you can spot the best-performing personalisation messaging, visuals, and signposting strategies. You’ll find CRO and A/B testing are an effective combination for creating experiences that resonate better with consumers and increasing website performance.
- Predictive analytics – For this technique, you can use propensity modelling to predict the likelihood of future action based on historical user activity. As such, you can pre-empt customer needs, delivering the right message to the right person at the right time to provoke a specific event.
- Churn analysis – Here, you’re studying historical churn data to make churn prediction possible. By analysing churn data, you can identify the moments when a personalised customer experience could make the difference between a customer remaining loyal or going to a competitor.
- Web scraping – Extracting data from websites can reveal customer behaviour, preferences, and interests, which you can use to tailor your messaging, product offerings, and engagement strategies. It’s a great way to pull information from review sites and conduct customer feedback analysis and sentiment analysis.
- AI – With its ability to continuously learn and adapt, AI is taking customer experiences to the next level, supporting real-time personalisation. Through advanced technology, it can adjust recommendations and tailor experiences the moment a customer interacts with a brand across any one of multiple touchpoints.
What happens when you get personalisation right?
The evidence that personalisation works is pretty conclusive. Take a look at some of the leading personalisation practitioners and the results they’re achieving.
- Netflix
More than 80% of content viewed on the Netflix platform is discovered through personalised recommendations. Indeed, the recommendation algorithm is so powerful that it influences content producer decisions. Netflix uses personalised customer experiences to attract and retain subscribers. It curates viewing suggestions based on user preferences, viewing history, and behaviour patterns. The company also offers customised interfaces and personalised thumbnails as part of its personalisation strategy. It runs about 250 A/B tests annually, involving 100,000 users per test, which shape content and image decisions.
- Spotify
81% of Spotify users have said personalisation is the best thing about the service. Spotify offers personalised playlists, such as Discover Weekly and Release Radar, that are effective at keeping listener engagement and increasing retention rates. Its Spotify Wrapped, which is a personalised recap of a user’s listening habits over the past year, is now a major event around the first week of December. In 2022, over 156 million users engaged with Wrapped. The personalised music summary, which is designed to be shareable on social media, triggered 400 million posts on X (formerly Twitter) in just three days. Spotify uses machine learning and AI to analyse customer data. It applies collaborative filtering to identify common interests and recommend similar songs. The service also uses natural language processing to analyse social media, blogs, and news articles and to suggest songs based on public opinion. All this works as Spotify’s active users grew to 626 million by mid-2024.
- Ocado
Ocado specialises in online grocery shopping and delivery. Rather than running physical stores, it operates customer fulfilment centres. The company ensures timely deliveries and high customer satisfaction by analysing customer orders and logistics data. An enterprise data platform allowed the company to increase the number of personalised campaigns by 10 times. Through greater personalisation, the company also improved customer satisfaction by 5% and reduced churn by 2%. Moreover, the focus on personalisation has resulted in gains across other core business KPIs, such as a 13.5% increase in subscriptions to Smart Pass, Ocado’s delivery membership.
Where to go from here
Admittedly, Netflix, Spotify and Ocado are at the cutting edge of personalisation. However, they demonstrate how powerful a personalised customer experience can be at moving the needle on a wide range of KPIs.
The good news is that you can make significant strides in your personalisation strategy simply by leveraging your primary data. Then, it’s really just a process of developing that strategy and advancing your use of data and analytics to see greater returns.
The truth is that personalisation is critical right now, and companies need to get it right the first time or risk falling behind their competitors. At Ipsos Jarmany, we have the experience and expertise to help you on your personalisation journey, just as we do for many customers. So please don’t hesitate to get in touch.
We can start a conversation on personalising customer experiences whenever you’re ready.
