Want To Know How Your Customer Feels In Real-Time? Use AI

Using AI, you can segment your customers down to the level of a universe of one. With such a good target base, you can develop personalised content, deliver it in a targeted way, and help drive engagement.

In the near future, organisations that excel in personalisation will outsell others. Personalisation in marketing has been around for quite some time now. It began with replacing “Hello customer” with “Hello Maryam”.

Brands send marketing messages that are specially crafted for the consumer. For instance, they come as emails during weekends, when consumers check their mailbox and app push notifications during lunch hour because generally, people check notifications on their phones. The brand knows what kinds of clothes consumers like and sends recommendations that suit their tastes. Seeing the purchase pattern, during the first week of the month, consumers get reminders about stocking up on groceries that they might run out of, based on their past purchases, which shows that the brand cares.

And that’s what hyper-personalisation is. With hyper-personalised marketing, the content, products, and services are tailored to meet the needs and want of every customer. This is accomplished by leveraging all forms of customer data-demographic and profile data, browsing patterns, geographic location, purchasing and real-time behaviour data across multiple channels and touch-points.

Importance of hyper-personalisation

More than 80 per cent of consumers want brands to understand them better and know when and when not to approach them.

A couple of years ago, demographic and behavioural-data based segmentation was the most effective tool for marketers to go beyond cookie-cutter marketing and deliver personalised experiences.

However, today’s customers are more tech-savvy and better informed than ever before. When consumers are bombarded by marketing clutter, they are almost always distracted and pressed for time — they expect brands to convey precisely the message they want or need. Whenever your content fails to resonate with your user, you miss an opportunity to engage him, provide a bad customer experience, and endanger your relationship.

What matters for today’s customers is a hyper-personalised experience. According to?cmo.com , 42 per cent of consumers would pay more for a friendly, welcoming experience, and 52 per cent would pay more for a speedy and efficient customer experience.

Deliver hyper-personalised customer experience

If you know “what has happened” and can identify patterns in the behaviour, you can predict “what will happen” and then decide “what needs to be done” to get the desired outcomes. In other words, you can deliver hyper-personalised customer experiences through AI-powered marketing.

AI and machine learning are all about understanding those patterns from data, deriving meaningful insights, and creating personas. You can deliver hyper-relevant, hyper-personalised content experiences to these personas.

You can send an email with personalisation using the customer’s name in the subject line. With AI-powered insights, you can still send a hyper-personalised email based on an item the customer recently browsed on your site. The subject line and send time can also be optimised to increase response rates.

How does AI-powered hyper-personalisation work?

AI runs on data. The AI engine learns from the historical customer data and teaches itself to predict customer behaviour by analysing historical data.

In AI, patterns are generated based on the customer’s profile, social interactions, and behavioural data – why they responded to an offer, why/when they clicked an email or SMS, and preferences, likes, and dislikes. Based on these insights, you can then target your marketing efforts. Data is, therefore, at the centre of any AI-based marketing strategy. Only when the data is connected and pulled from across channels, devices, and data sources can you start to extract the real value of AI-based personalisation.

All technologies and platforms that collect customer data must be integrated to achieve a truly unified customer view. Connecting your systems tightly will make your AI system more effective.

How does AI power hyper-personalisation?

Using AI, you can segment your customers down to the level of one. With such a good target base, you can develop personalised content, deliver it in a targeted way, and help drive engagement. The following ways in which AI enables hyper-personalisation:

Predictive marketing:

One of the most critical aspects of hyper-personalised marketing is understanding what the customer will do next. This enables you to tailor your marketing strategy for maximum effectiveness. AI can tell you whether a customer is churning, will make a purchase, or needs some nudge to move down the funnel. Using these powerful insights, you can stay ahead of the competition and deliver a relevant experience. Netflix’s long list of recommended movies and TV shows is a fantastic example of a personalised user experience powered by AI.

Customised contextual content:

Hyper personalisation is about making it easier to customise marketing to your consumers’ requirements and tastes and target them at the optimal time in their journey. You may create highly contextual and relevant communication by combining behavioural and real-time customer data with AI insights and tools.

For example, AI may analyse client demographics, current geographic location, most frequent purchase times, communication preferences with companies to give you a clearer picture of how to engage with them. While the material is essential, it isn’t meaningful without context. In other words, hyper-personalisation enables content marketers to be more proactive in communicating with their target consumers by making their material more contextually relevant.

Real-time customer support:

Today’s customers seek instant responses and resolutions to their problems. Customers value real-time customer service. Given the growing client base and their expectations, it is hard to provide this level of service at scale. But then there are AI chatbots for a real-time conversation, answering basic queries, tracking and fulfilling orders, and resolving minor difficulties.

Seeing the scenario, we can say that, sooner or later, the average person will have more conversations with chatbots than with their partners. While this can be heartening and concerning simultaneously, the fact remains that chatbots are the thing now.

Accurate attribution:

“Most marketers rely on reporting rather than genuine attribution,” says Matt Scharf, Adobe’s Director of Integrated Marketing Analytics.

Attribution is essential when evaluating the success of your activities — understanding the customer’s whole buying journey, which marketing channels create revenue, and what types of content promote conversion, engagement, and retention. It’s tough to connect with so much client data coming in from many sources.

Modern AI attribution models can help with this. You can evaluate how effective each touch-point is in driving business KPIs and optimise your marketing plan beyond typical attribution approaches. You can handle each user appropriately if you know what works for them.

AI has enormous potential to increase your brand’s engagement and conversions. To summarise, the entire game relies around gaining a firm grasp on your data, embracing the powers that AI-based data analysis gives, putting them into practice, and constantly adjusting yourself. The key to long-term success is staying relevant.