We gained respondents’ views on why they like personalisation by asking them to rate the advantages and disadvantages on a five-point scale of strongly agree to strongly disagree. Sentiment improved consistently across the board, with more people agreeing or strongly agreeing with positive statements about personalisation in 2021 than they did in 2019. 

What consumers like the most has stayed the same, with time saving, helping people find new products, or helping them find exactly what they need securing the top three spots. Notably, the biggest increases came from the ‘strongly agree’ ranking, where there was an average 5% increase in the volume of people strongly agreeing with statements. 

Whereas sentiment has improved for the positive associations with personalisation, it has largely stayed the same when it comes to the reasons people dislike it, with some minor fluctuations for individual statements. The top three reasons why people dislike personalisation are that it can be ‘irrelevant’, ‘creepy’ and ‘unsecure’.

Overall, feelings are strong both for and against personalisation. However, positive sentiment is stronger than negative when reviewing these insights holistically, meaning that consumers like and see the benefits of personalisation more than they dislike it. As in 2019, personalisation is still in the domain of being perceived as both good and bad, suggesting that not enough progress is being made by retailers. 

Taking inspiration

The days of personalisation being little more than a first name-addressed email and a ‘happy birthday’ discount are long gone. Digital-first businesses are raising the bar and, in turn, customer expectations. Take Spotify as an example, its daily playlist recommendations and annual ‘Spotify Wrapped’ campaign (recently complemented by its ‘Only You’ campaign), deliver a true one-to-one, personalised experience for users. 

These activities are built on data, which is applied in a way that creates an engaging experience for users that isn’t at all perceived as ‘creepy’. The campaigns are also delivered without any immediate conversion, strengthening the value exchange as users don’t feel like they’re being sold to, yet we predict that these activities have a huge positive impact on Spotify’s customer loyalty and retention.

Driving customer loyalty

The e-commerce industry is still some way behind the likes of Spotify, with personalisation efforts being largely focused on short term conversion through email marketing and retargeting methods, rather than how it can benefit brand-consumer relationships in the long term. But in order to catch up, focus needs to be switched to creating a strong value exchange through experience which, in turn, will have a positive impact on sales and loyalty. 

The opportunity to strengthen the link between personalisation and loyalty has seen minimal progression between 2019 and 2021. Just 24% of participants said that personalisation makes them more loyal, while the majority (62%) said it makes no difference. Meanwhile, 38% believed personalisation was adopted by brands simply to make them spend more money. Another 39% felt it was to make them spend more as well as make them like the brand more. 

Getting to know you

With the majority of negative consumer sentiment for personalisation stemming from a lack of relevancy, greater focus needs to be put on gaining a truer picture and understanding of customers in order to make more relevant recommendations. Asking consumers questions was one of the least common types of personalisation experienced by study participants, yet the vast majority (70%) found it one of the most helpful. 

Asking questions or for feedback is one of the most basic tactics that many brands either don’t get right or don’t even touch. But by taking more of an interest in customers, brands are more inclined to know what they want, make more relevant suggestions and improve conversion. Any attempt to gain more in-depth information from consumers should be built into an experience in support of creating a strong value exchange between brand and consumer. 

DEPT® worked with Lyst to do just this, creating a campaign that encouraged customers to ‘discover their fashion DNA’ that gave the brand lots of valuable insights to inform personalisation tactics. Using relatable, scenario-led questions in a quiz format, Lyst was able to effectively gather lifestyle-oriented data to generate a better understanding of its users, based on their preferences. As this information was gathered, it was directly linked into Lyst’s existing database of website analytics, paths to purchase, onsite user journeys and favourited products or categories. Adding this new data and filtering results into categories enabled Lyst to formulate well-rounded user personas and frame future marketing campaigns with highly personalised touchpoints. The quiz indulged customers with expert design and interactivity to provide them with insight into how their lifestyle preferences position them on a global scale, a strong value exchange for Lyst to gather user data. 

Personalisation provides many benefits for retailers and brands, but it needs to offer consumers true value in order to progress. That’s why the focus of future efforts needs to be shifted towards seamlessly and intuitively guiding customers through a brand journey that makes sense. 

Download our report to find out more or get in touch with our experts to learn how DEPT® can help your business accelerate its personalisation strategy and get ahead of competitors. 

When we asked if consumers would be willing to share more data with brands if it would improve personalisation, 56% of participants said yes. This is a 4% increase on 2019, widening the gap between those who would and would not to 12 points, rather than four. Despite this, when asked about the data they would be willing to share, we found that consumers are less willing to share specific types of information with brands than they were in 2019, highlighting the gap in consumers’ understanding of what ‘data’ is or can be. 

56% of consumers would share more data to improve personalisation

The majority of consumers are more comfortable with sharing information about their preferences than information that has the potential to make them identifiable. The top three data sources that consumers are most willing to share are: favourite brands (59%);  hobbies and interests (58%); lifestyle choices (46%). It’s important to note that even these higher performing categories are, on average, 5% lower than they were two years ago, suggesting that consumers are not as comfortable sharing even these types of data as they were in 2019. 

Interestingly, when asked why they may be less comfortable, consumers are actually less concerned about the risks of sharing data than they were in 2019. The concerns have remained in the same order of significance with fear of spam marketing (60%), fear of data being sold (54%), and privacy worries (53%) taking the top three spots. However, there has been an average 7% decrease in these scores across the board. This could suggest that consumers’ digital maturity has accelerated during the period, and/or that they feel more in control of the data they share and, therefore, less concerned about the ‘risks’. 

There are clear discrepancies between consumers’ understanding of the link between data collection and personalisation. But it also seems that those who are aware of the link prioritise data protection over personalisation, with numerous comments saying that efforts are largely in favour of the brands as opposed to shoppers.

“There always seems to be a trade-off when it comes to supplying data to get a discount or offer. The retailers just use this data to predict your shopping habits or sell it on to other retailers.”

Data is key to improving personalisation, enabling brands to make decisions and implement actions based on insight rather than instinct. But it is also reliant on the customer voluntarily sharing certain information, and there is definitely controversy surrounding the topic. 

Although the majority of consumers say they are willing to share more data, by digging a little deeper we understand the boundaries consumers have set relating to that. We must not ignore that 44% of consumers said they would not share more information to improve personalisation. It is clear that people are still wary and unsure about brands asking for and collecting their data. 

44% of consumers said they would not share more information to improve personalisation

The perceived risks of sharing certain information with retailers and brands present a significant blocker to the future progression of personalisation. Building trust between brands and consumers will be key to breaking down these barriers. If brands are to focus on securing this information, they will need to drastically improve communications about how they use data, and demonstrate the benefits of providing such information (i.e.through well executed experiences), in order to build consumer trust and increase their willingness to share.

The opportunity to promote transparency and build trust may lie in giving consumers more control, switching to an opt-in approach to personalisation, or by creating preference centres where customers can manage their profile and levels of participation in personalisation. This would enable consumers to take control of the types of personalisation they want to receive, if at all.

Aside from the trust challenge, companies can still take action by better activating the data they already have. E-commerce data pools are vast. Brands have access to huge volumes of consumer insights that are not reliant on the customer providing them, such as previous purchases, recently viewed items, abandoned baskets, and social media engagements. The list goes on. 

What more data-proficient companies have in common, is that they understand how to best aggregate and action this data. They are connecting their various sources of consumer information within customer data platforms to gain a single customer view that can drastically improve personalisation and marketing relevancy. 

Abandoning data silos, CDPs collect and analyse customer information from a variety of different sources such as the CRM, web forms, in-store systems, email, social media and many more. This creates a single customer view that includes demographics, behavioural and transactional insights, helping businesses better understand customers’ journeys, wants and needs. CDPs assist brands in better identifying customer segments and understanding behaviour. When looking beyond data silos, unified customer data allows companies to prioritise and target users in different ways than before. When intelligence is applied to this strengthened customer view, companies can start to make decisions based on facts rather than instinct or opinion; driving sales by leveraging past trends to make future predictions. 

The need to invest in first party data is also growing in significance following Google’s announcement to move away from third-party cookies by the end of 2023. First-party data is fast becoming the cornerstone of all online activity, so brands that invest in strengthening their first-party data sources and strategies now will be future-ready.

Taking action

It seems that when it comes to personalisation, companies have fallen into the trap of repeating what others are doing out of fear of missing out. They recognise that to better personalise, they need better data, but little innovative thought goes into how to collect and activate that data. 

Personalisation needs consumers on side in order to progress. Download our report or get in touch with our experts to find out how DEPT® can help your business accelerate its personalisation strategy and get ahead of your competitors. 

There is a tendency in the B2B e-commerce sector to look across to the top B2C brands and play down the applicability of the features and techniques that make their sites market leaders. The idea that stylish sites and flashy features only fit the B2C model, while B2B should focus on the bread and butter options to fit the typically measured and professional tone of voice that many B2B brands use. This is misplaced thinking, based on the division of B2B and B2C. In reality, there are businesses, there are customers, and there is e-commerce. Shopper psychology spans across each; the features that allow B2C brands to excel in the online space are there because they work. Chiefly, personalisation.

Personalisation has always played a role in commerce. In the past, personalisation existed in retail as an in-store assistant, and in industry as a sales rep that would build a relationship with the customer over time, learning their needs, their pain points and how they liked to conduct their business. These approaches have always led to a much improved buying experience; faster, easier and more accurate. But these relationships take time to build; it’s a long term process of listening, learning and responding. And while human-to-human contact is still very much valued, digital technology, data tracking and analysis can bear the load. When implemented well, personalisation can speed up sales cycles and nurture prospects into loyal customers.

Advancements in digital technology have radically cut the time it takes to understand each individual customer and provide a personalised commerce experience.  This technology is widely available, often built in to your content management system; all businesses now have the ability to implement personalisation strategies into their marketing and commerce efforts. This is good news, seeing as smart personalisation engines used to recognise customer intent can lead to an average profit increase of 15%. The flipside to this, is that personalisation has moved from an added benefit of certain businesses to an expected feature across every experience. 33% of consumers abandoned a business relationship last year because of a lack of personalisation. This is a necessity, not a nice to have feature.

Utilising account specific data

When starting to think about how your business can use personalisation in its commerce sales funnel, begin by thinking about how the company can collect data about customers and visitors. It’s important to begin with data capture, as the implementation of features depends on the type of data collected.

For specific customers, data primarily comes through the account creation process: job function; past purchases; which pages they have previously visited on the site; their dwell time; on-site search history, and so on. If the current data collection on account creation is limited, build this out for future customers and consider requesting current users to update their profile with more information upon their next login. Rather than hiding the motive, make it clear that the company will be using the data for an improved, personalised shopping experience. This clarity will boost the numbers opting in to data sharing, as it clearly offers a mutually beneficial exchange.

Putting this in place, electronics manufacturer Omron was able to create a site that adapts to the needs of each visitor. By using information on the job function of each logged in visitor, the Omron site could dynamically adapt and funnel distributors, systems integrators, Omron employees and end users to the appropriate pages. This is a simple solution, using just one piece of data to adapt the site, but it has a major impact, with the ability to scale up personalisation based on further gathered information.

Making use of automatically collected data

Thinking about data capture also means thinking about the information that is automatically collected when a user visits the site, whether logged in or not. Their location data, the search term that brought them to the site, their onsite user journey –  all of this information can inform your personalisation approach. Personalisation based on this information is subtle, possibly unnoticed as the visitor explores the website. They may not recognise the personalised experience, but will come away thinking that the shopping experience was quick and easy.

This also applies to classic customer segmentations, a general grouping based around shared behaviours. Personalisation doesn’t always mean single individuals. These segmentations can be useful when thinking about broader data automatically collected by new visitors to the site, as the depth of information isn’t there to create an individual response. As an example, an electronic parts company could use site search data to establish a segmentation that prominently displays associated purchases to visitors.

With an understanding of how data is collected, your business can begin planning the execution. At this stage, think in terms of what can be done onsite and off-site. While it is easier to control the onsite content and design, focusing solely on the website can see businesses missing out on the opportunity to fine tune their contact with customers through advertising and direct messaging.

Dynamic content

Onsite, dynamic content is a useful tool to make use of. This is content that adapts based on the data that is fed into the CMS, whether it is account data, previous purchases, search terms, and so on. The most obvious use is often found in the leisure and tourism space; if a visitor clicks on a number of pages relating to Italian destinations, the site can adapt the background images on more general pages to show Rome, Venice and Florence. 

In the B2B space, dynamic content can be used to display relevant information, based on what is known of the customer. If they have listed their job function as logistics, they can be shown contextual information on delivery times and options, while a member of the finance team will see more about pricing options and different payment plans.

Accelerating everyday tasks

Speeding up common processes is another use, particularly helpful when looking to keep long term customers engaged. There will be a number of actions that returning customers have to redo with each visit, the most obvious example being adding items to the basket.

This is particularly important for B2B commerce as orders can be large and complex, and customers are more likely to repeat their orders when compared to B2C. Improving reordering was a key feature when developing Brenntag’s new commerce platform, Brenntag Connect.

As a chemical distributor, Brenntag has a strict process when allowing new customers to use their service. Customers are typically placing large, identical orders, leading Brenntag to create an automation service that places repeat orders and provides relevant contextual information when customers need to make an adjustment. This is a clear indicator of why it’s important to remember that personalisation is not fitting to how customers buy, it’s fitting to how customers behave.

Supplying more information to upsell

When customers are returning to reorder from your company, there is an opportunity to upsell existing products and promote new ones. This goes beyond ‘customers who bought X also bought Y’. This form of personalisation should aim to suggest alterations and explain the reasoning, based on the specific customer’s order. Think of it as a digital representation of the sales rep relationship, understanding the developments in a customer’s business and reacting with new solutions.

It can also be developed into a website feature, an interactive problem solving flowchart or chatbot that allows visitors to input their problem or need and see what solutions the company would suggest.

Optimising site speed

Not every on-site personalisation improvement is interactive and clear for customers to see. Adding in predictive loading is one example, a feature that speeds up the load time for each page on your site based on similar customer journeys.

Customers may never realise that the site they visit uses predictive loading, but they will notice if a site is slow to load. Selling needs to be as smooth as possible; slow loading leads to a larger bounce rate. Installing features, like predictive loading, that uses the information gathered when analysing personalisation can ensure the process never stalls.

Off-site actions

Personalisation also applies to actions that the company makes off-site. Email is one area, automated workflows for customers that left the site without checking can bring them back, boosting conversion through reminders and specialised offers. This can similarly be used for surrounding purchases, following the frequency of repeat purchasing or the typical time it takes for a customer to branch out to a new product.

Also consider how the purchasing journey exists across different touchpoints such as apps, social media and face-to-face meetings. Is it easy to bring up the customer profile and optimise their order based on this information? This kind of integration creates a seamless experience, perfect for B2B’s longer, omnichannel purchasing journeys.

Facilitate an easier commerce experience

In each recommendation, the end goal of facilitating a faster, easier, more accurate commerce experience remains the number one priority. By hitting each aim, the business makes each customer more likely to checkout, more likely to return, and more likely to talk to people in their industry about how great purchasing from your business is. These improvements build up, a snowball effect that ultimately results in increased sales and larger, loyal customer base.

Personalisation is an important pillar of digital marketing strategies. With the rapid evolution of marketing, technology come greater capabilities at the hand of marketers. Investment in MarTech is rising and the bar is set higher. Consumers expect more than a list of products and services when they visit a website. Whether they realise it or not, consumers want businesses to provide them with experiences tailored to their specific needs at that moment.

How brands connect with consumers via personalisation tactics was the topic of discussion amongst panelists at a recent DEPT® event. The panel of Floris Oranje, Managing Director of Managing Director Digital Marketing at DEPT®, Sally Nowroozi, Senior Business Consultant at Salesforce, and Angus Jenkins, Head of E-commerce at Figleaves shared their opinions on the state of personalisation. Diana Pearl, Staff Writer at AdWeek, was the moderator for the breakfast event in London earlier this month.

“Approach personalisation from an audience perspective to serve them better, in a more purposeful way, as a means to understand their needs and guide them through the journey. The approach should be more helpful and less obvious from a sales-perspective”, Sally mentioned, starting the dialogue.

“At Figleaves, there is an added element of complexity, in terms of buying women’s lingerie and supporting the user as they funnel through thousands of intimate products. We don’t want to overload the customer with choice or, equally, compartmentalise them in a space they don’t want to be in. If we narrow down, we run the risk of rejection for being too personalised,” said Angus.

“Previous purchases are our highest value statistic for personalisation, we’re able to get an idea of preferred style, brands, and size. We want our customers to browse and serve up discovery, or else we just become a commodity business and that’s not the brand strategy,” Angus continued to comment.

“Figleaves is bold enough to try different approaches to find out what our audience appreciates and sometimes actions can cause frictions in the UX, or add additional steps. We’ve learnt that it’s all about the execution, ensuring objectives align with relevance.”

A consumer research study conducted by Dept involving 1,000 online shoppers in the UK, reveals one of the most frustrating points with personalisation is being sent recommendations and offers that are not relevant.

Floris said, “This is often as a result of users purchasing an item as a one-off, as a gift, or someone else browsing through their account. The more user-data brands can compile about their customers, ideally first-hand, the more they’re able to accurately tailor touchpoints and enable personalisation to become a useful asset.”

“For instance, customers want to track packages and get updates, but they need to log in and opt-in to be contacted. There needs to be a way to communicate that. We’re constantly battling a balancing act with transparency and how to explain why we need data and what we’re doing with it,” Angus added in agreeance.

“Dynamic data and advancements in MarTech will evolve personalisation, but it needs to be a two-way street with consumers recognising the benefits and providing their details for the sake of personalisation. Connecting the dots between consumer identities, structured and unstructured data will be fundamental for brands to progress, creating an intuitive and channel-less way for brands to speak with customers,” said Floris.

Sally added, “Brands need to stop thinking about personalisation as a project, but use what they have and put on a human hat to incrementally improve design, strategy and marketing. People think of loyalty as a programme, but it’s actually about how you serve your customers and how you define loyalty. Shouldn’t loyalty be defined as a greater definition for the value of engagement?”

When asked how their favourite brands use personalisation, the panellists commended Amazon’s seamless Chatbot feature for easing complicated processes, like returns. The make-up brand Sephora was mentioned for effectively integrating their much-loved, in-store customer service online with a customisable beauty profile. Spotify music player was also acknowledged for ‘getting it right’ for delivering results that don’t feel intrusive.

As an ending note, the trio concluded, a customer’s experience is just as good as the products themselves, and all attempts to connect should be relevant and add value to the consumer.

For more insight on the consumer’s view of personalisation, download DEPT®’s free Whitepaper Report.

Did you know, over 50% of opened emails are deleted within two seconds. That’s right, we’ve all done it. We all receive emails that we simply don’t care about. You know the kind: irrelevant, impersonal, pushy and sales focused. It’s not often what you want and definitely not what you need. This email was probably auto-generated because companies realise they need to stay in touch with their customers but aren’t sure how to best do this. So, what’s a brand to do?

Start delivering personalised, targeted and contextualised emails with a deeply relevant message. Many marketing automation platforms can actually help you accomplish that. This ensures your email gets read rather than trashed. Personalised emails can improve click-through rates by as much as 14% and can drive revenue by as much as 760%.

Two sides of the same coin

Now, there are two types of personalisation: dynamic and hyper. Dynamic content is the “traditional” version of personalisation. This might include the name, title, organisation and purchase history of a person. This is a good practice, one that many brands already use, but it’s often not enough to capture the user’s attention. However, hyper-personalisation takes this up a notch and utilises behavioural and real-time data to create highly contextual communication that is much more relevant for the consumer.

Let’s look at dynamic personalisation in action. A consumer might receive a basic email from brand X suggesting to them other items they might like. These recommendations are based on their recent purchase(s), browsing history and items that are usually bought together by other customers. Very general information that every brand has access to when a client purchases something on their website.

However, hyper-personalisation is much more tailored. This is the place where all the data comes together. Here an email with recommendations will be based on similar notions as mentioned above. But, there’s more! Website behaviour such as how much time a person spends on each page and items they hovered over are incorporated. Also, recommendations will also be based on gender, age, interests, hobbies and preferences, spending habits in addition to geographical data. For example, if you know the location of the customer you can offer them shop specific promotions. All of this information is combined to provide more relevant content to the consumer transforming them into (hopefully) return customers.

The three-step process

To apply hyper-personalisation to your emails, you can use AMPscripts from Marketing Cloud. AMPscript is a scripting language that you can embed within your HTML emails, text emails, landing pages, SMS messages, and push notifications from MobilePush. The system processes the script at the point where you include it in the message to render content on a subscriber-by-subscriber basis. The Marketing Cloud application handles all AMPscript calls at the end of the email sent.

This tool allows for personalisation per specific subscriber, which means that every subscriber is going to see a different email based on their interest and data.

To best implement this practice, there is a three-step process you can follow.

Personal is better

In an era where individualism is a trend, hyper-personalisation is the key to standing out amongst your competitors. As shown, you can easily implement this practice in three easy steps. And this is just the beginning. If you have all of this data, you can take it to the next level and, say, create a life cycle of tailored emails for consumers from welcoming them, to recommendations and personalised reactivation if needed to keep them interested. You could even take this up a notch and customise website per consumer based on what you know about them, giving them a truly tailored experience across all platforms. As Dale Carnegie once said, “a person’s name is to that person the sweetest and most important sound in any language”.