Want to Predict Customer Behaviour? Look for Hyper-Personalisation to Take your Marketing Up a Notch

Customer Experience is the Endgame for Marketers and the advancement in MarTech, esp. Marketing Automation in the form of Deep Learning is driving the gamut.

Posted in Customer Experience, Hyper Personalisation, on June 19, 2019, 12:03 p.m. by:

John Doe
Aakanksha Sharma

Content Marketer

A business’s focus on the evolution of marketing technology (MarTech) is important for their need to differentiate from the competition. On its parallel, there is another maxim – personalisation for B2B and B2C customers, who are now sustaining their roles as tech-savvy, independent researchers. Their devices are now swamped with more marketing messages, they can now access more information than before and in this manner, carry out more research. For businesses focussing on delivering the right message to the right customer at the right time, the present is the perfectly right time to look beyond the ‘basic volume’ of data personalisation engenders. By basic, we mean – ‘Who is the customer?’ ‘What products they are spending money on?’ ‘what channels they are active on?’. The present is the right time to take a transformational upswing from ‘personalisation’ to ‘hyper-personalisation’. (Stay around for an informative discussion on personalisation Vs hyper-personalisation & how they are fuelling the modern marketing.)  

Marketing Automation powered by AI and Machine Learning is now the ‘Crystal ball’ of the MarTech to predict Customer Behaviour. Technology like Deep Learning is taking personalisation up a notch. 

The previous year report published by Temkin Group states that a business with $1 billion annual revenue records an increased average revenue of $823 million in over 3 years, with improved customer experience. 

Marketers are leveraging data from various sources to get a single view of the customer. Now the obstruction here is, channels have grown tremendously (email, website, mobile (e.g., SMS, push notifications), social media marketing, display/banner ads, advertising on social platforms, organic search, paid search, video advertising) and the path to gain a single customer view is compounded with elevated customer expectations for 1-to-1 experience. In order to connect customer experiences, marketers are coordinating across channels but they somehow are, lagging in developing the marketing message gradually from one channel to another.

Let’s take it in this way – A personalised email offer for a coffee maker is sent to a customer A. this personalised marketing message succeeds its intent and the customer purchases the coffee maker through the link inscribed in the mail but still has to see the advertisement of that same product everywhere on the web. This leaves the customer with an impression that the business is not concerned for their actions & needs – that they have already purchased the product. Embracing AI and Deep learning enable marketers to draw more from cohesive customer behaviour which fuels the leap to hyper-personalisation. 

AI is transforming marketing efficiencies with tactics like lead scoring with predictive AI and product recommendations on the basis of customer behaviour. Deep learning, which is a subsidiary of machine learning has augmented marketing automation and has helped businesses develop 1-on-1 customer experience across different touchpoints. Here are three examples –

Uncovering deeper patterns in the customer data 

Businesses leveraging Machine Learning for marketing garner history of interactions, like purchasing habits, behavioural traits and digital preferences to personalise their brand’s customer experience. With Deep Learning technology embedded automation draws customer intent from the customer behaviour to identify the deep patterns from the data like their interaction history. 

Customer returning to a fashion commerce website to search for a pair of stilettoes after purchasing a dress, will not be swamped with similar dress advertisements. Deep learning takes a step ahead from transactional data & takes customer’s intent into consideration and thus, brands will be able to give product recommendations for a complete party ensemble.            

With deep learning, marketers are able to proliferate from real-life next-action predictions by uncovering the patterns within the patterns.

Driving Customer Retention for Long-term Growth

With every customer, the process to foster their association is important for maintaining the percentage of customers who are satisfied with services/products. It includes a decent range of mathematics that involves newly acquired customers and those of who churned. Deep learning in Marketing Automation is improving the customer retention rate of businesses, to augment their profitability. It takes marketing efforts steps ahead from delivering the right message to the right person, at the right time by giving highly relevant and hyper-personalised suggestions. How? By concurring a customer’s spending habits & patterns, their taste and personal preferences with superficial factors like weather.

Synthesizing Customer Behaviour 

Machine Learning optimises the best course of action for complex decision making with recommendations. Modern marketing automation systems synthesize customer data with deep learning algorithms to predict customer’s behavioural patterns and thus, predicting their ‘next-buying-decision’ and future trends for a greater customer base. So instead of vague predictions on customary data, they offer predictive revelations like – next purchase of your customer, preferable time of buying and right discount or perfect offer to extend to a particular segment of your customers.

Learn more about how Intelligent Automation is looking beyond conversations, to customer intent.

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