In today’s increasingly competitive and unpredictable marketplace, delivering contextual personalisation in digital marketing is no longer a “nice to have,” but a basic requirement customers have come to expect. Consumers prefer brands that feel like they listen to them, understand them, and pay attention to their specific wants and needs as fully-rounded individuals.

What is Personalisation in Marketing?

Personalisation is a way for brands to contextualise the messages, offers, and experiences they deliver, based on a unique, single customer view (SCV) profile. For data-driven, customer-centric marketers, hyper-personalised experiences are becoming a critical part of managing and optimising the customer journey. In fact, 75 % of business leaders say personalisation is table stakes for digital experiences, according to a Twilio report.

While hyper-personalisation software and tactics in digital marketing have been around for a few years now, consumers today are much more digitally savvy than they were just a few years ago. These consumers now expect the companies they interact with to provide exceptional, digital-first customer experiences.

This massive shift in consumer behaviour and an exponential increase in data volume, velocity, and complexity requires a far more robust and strategic approach to hyper-personalisation than before.  

Leveraging hyper-personalisation for customer and business value is essential for organisations to differentiate themselves and remain competitive. Effectively planned and executed hyper-personalisation can help increase engagement and improve satisfaction by delivering contextually relevant and personalised customer experiences in real-time.

It’s time for modern digital marketers to reevaluate their current marketing strategy and update their personalisation tactics to more accurately reflect the acceleration of consumer behaviour and digital transformation over the last two years.

State of the Personalisation Market

As of 2022, the personalisation market is healthy and growing at a solid rate.

According to 360i Research, the global hyper-personalisation software market was estimated to be $764.30 million in 2021 and is expected to reach $943.25 million in 2022, at a CAGR of 23.58 % to reach $2.72 billion by 2027.

The real advances in personalisation are happening due to the influx of artificial intelligence (AI) and machine learning (ML) technologies to create more intelligent, automated, and actionable software.

According to BusinessWire, analysts forecast the global artificial intelligence-based personalisation market to grow at a CAGR of close to 13 % between 2018 and 2022. Back in 2017, website hyper-personalisation held the largest market share, accounting for nearly 34 % of the market. In 2022, expect email personalisation to surpass website personalisation to become the leading personalisation element, accounting for a market share of 35 %.

The recommendation engine market size is projected to reach $12.03 billion by 2025, up from $ 1.14 billion in 2018, with a CAGR of 32.39 % between 2020 and 2025, according to IndustryARC.

Some Challenges Persist

Even with all this positive growth, some challenges remain for marketers and companies that want to pursue a more customer-centric business strategy.

Forrester’s 2022 Predictions found that heightened expectations for digital experiences in the wake of COVID-19 will be one of several critical business trends going forward. Today, 8-out-of-10 consumers see the world as digital first. The problem for marketers is that they lack the necessary data to personalize customer experiences. 75 % of efforts to create autonomous hyper-personalised engagements will not meet ROI goals because of inadequate buyer data.

Finally, a Twilio survey found that there is a gap between how marketers and consumers perceive personalisation. 85% of businesses believe they are offering personalised experiences, but only 60 % of consumers agree. It seems there is a lot of opportunity to modernise personalisation programs to be more reflective of consumers.

Why AI Machine Learning Hyper-Personalisation Matters

The surge in online interactions since the pandemic escalated customer expectations, giving consumers more exposure to superior hyper-personalisation, and raising the bar for everyone else. From web to mobile and in-person interactions, consumers now view hyper-personalisation as the default standard for engagement. there are many distinctions between hyper-personalisation vendors that the canny CMO needs to acquaint themselves with.

71 % of consumers expect companies to deliver personalised interactions, and 76 % get frustrated when this doesn’t happen, according to a McKinsey report. Consumers aren’t intimidated about switching brands or looking for a better experience, either. The report found that 30-to-40 % of U.S. consumers have switched brands or retailers in pursuit of better prices, product availability, quality and purpose.

It’s not all about customers, though. In the end, it’s all about the bottom line. The McKinsey report found that companies that leverage hyper-personalisation effectively generate 40 % more revenue than companies that don’t. Hyper-personalisation can reduce CAC by up to 50 % while increasing marketing spend efficiency by up to 30 %. And, according to Evergage, 86 % of marketers have seen a measurable lift in business results from their hyper-personalisation campaigns.

The numbers don’t lie: hyper-personalisation is good for your customers, prospects, digital marketing performance, and business outcomes.

Hyper-Personalisation Best Practices

Digital marketers who leverage hyper-personalisation effectively follow these best practices to ensure successful customer-centric business programs.  

1. Embrace a Data-Driven Mindset 

How data-driven are you and your team? Any working professional in intense working conditions appreciates that many decisions have to be made quickly to meet deadlines or other internal expectations. Infuse best practices surrounding data-driven operations into thought processes and behaviour, so that even on-the-fly decisions can be anchored in good data-driven methodology. 

Data-driven marketers will embrace data and analytics as a foundational step to identify opportunities and create operational efficiencies. They examine the full customer lifecycle, focusing on areas where the most value is found. Data-driven marketers also leverage customer segments and microsegments and will factor in data like behavioural, transactional, and engagement trends into their strategy. Be aware that segmentation is marketing marginalisation, as segmentation is not personalisation.

2. Maintain Clean Data

There is an old saying in computing called GIGO: Garbage in, Garbage Out. If you input poorly formatted or unclean data into any system, regardless of what type of system it is, you will get outputs that are only as good as what you put in. For data to be used effectively in personalisation programs, you must have your data prepared for ingestion into a data management solution, like a Customer Data Platform (CDP). Many modern enterprise-grade CDPs will offer data integration capabilities within the platform after the data has been ingested, so it’s an important step to think about the quality and cleanliness of your data before it ever goes into any system. 

3. Invest in Activation and Analytics

AI machine learning hyper-personalisation is an investment in technology, that is capable of the highest returns in marketing spend. Considerations have been applied such as the difference between deep learning and neural networks. Data-driven marketers should plan to develop scalable content and AI-driven functionality so they can respond to customers’ needs in real-time.

4. Choose the Right MarTech

Hyper-personalisation-focused marketers invest in the right MarTech for a particular goal. For instance, if you need to gather disparate data from multiple silos and integrate them into a single customer view profile, a CDP may be the appropriate MarTech solution.

5. Follow an Agile Operating Model

Hyper-personalisation-oriented marketers are dedicated to an agile operating model, both internally on their team and across the enterprise. Scaling hyper-personalisation requires teams that cut across marketing, product, business, analytics, and technology, of course, AI has enabled this whole system from it being unimaginable just a few years ago.

Future Hyper-personalisation Trends 

While brands may have started their hyper-personalisation journeys a few years back, many simply purchased an add-on for their content management system and did some website personalisation. Looking forward over the next five years, the major trends are in hyper-personalisation.

Omnichannel 

Look for hyper-personalisation to move towards full multi-touch, omnichannel marketing experiences (mobile, email, SMS and app hyper-personalisation) driven by expanding customer expectations for a more unified brand experience across the whole customer journey.

One-to-One Communications 

With customers wanting brands to recognize them as individuals, it is incumbent for brands to develop more personal, one-to-one relationships with their customers. This individualised communication style is possible with machine learning hyper-personalisation driven by the right MarTech. With this type of interaction, you will be able to focus on customer long-term value as a key metric for maximising your most valuable customers.

AI-Driven Personalisation

There are several areas where AI is also driving advanced personalisation capabilities.

• Chatbots using natural language processing and machine learning can understand the context of a sentence and can carry on full conversations with a customer.
• AI can direct customers towards relevant content they need and provide targeted, personal responses, and personalize content based on purchase history, customer service tickets, and other behaviour.
• AI allows brands to provide customers with personalised ads based on demographics, purchase history, and browsing.
• Recommendation engines surface products and services based on a customer’s previous purchase history.
• AI-powered customer sentiment analysis analyses voice, images, and behaviour to better understand emotional states.

Looking Forward

Companies that achieve the best results from hyper-personalisation view it as an organisation-wide opportunity, not just something that benefits marketing or customer service.

Brands that leverage data-driven, customer-centric best practices look for long-term drivers of growth and focus more on emerging KPIs like customer lifetime value (CLTV), rather than focusing solely on short-term growth or immediate opportunities.

With a focus on CLTV as a key metric, companies can use hyper-personalisation to increase their revenue, improve retention, reduce churn, and create brand advocates.

Today, tomorrow, and well into the future, hyper-personalisation will continue to be a critical component of a brand’s digital marketing strategy.