Where will your customers be next?

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Predictive marketing driven by artificial intelligence and advanced analytics is what will define the next generation of digital business.

As a B2B marketer, you already know that customers today are better informed and more aware of their requirements. So the traditional way of marketing a product or solution to them no longer works as effectively.

The customer buying journey has become more complex. It is no longer just about selling a product or a solution and closing a deal; the buyer journey goes far beyond a sale, and toward what your clients might want next. Whether you are a B2C retailer or a B2B solution vendor, the key to remaining successful is to have the knowledge of where your customers are now and where they are going next.

That is where predictive marketing – a subset of predictive analytics – comes into play. The next generation of marketing uses big data and artificial intelligence to analyse and predict how, when and where your customers will be next and what they might be looking for.

Emergence of predictive analytics

So why is there a need to predict where your customers will be? The obvious answer is that the market is more competitive now than it’s ever been, and your customers are far better informed. They also have more touchpoints from where they can get information, to likely be targeted by your competition.

According to Gartner predictions1, by 2020, 40% of the investment in business intelligence made by organisations will be for predictive and prescriptive analytics.

So how does predictive analytics help an organisation in its marketing initiatives? The technology is based on machine learning and improved big data aggregation. In a predictive analytics process, the solution uses historical data — that your marketing and consumer behaviour tracking efforts might have generated — to predict future actions that your targeted customer might take. Predictive analytics identifies patterns and develops forecasts to help you make a better marketing decision.

A good thing about this paradigm shift in the era of digital business is how easily you can now amass client data. Even in the B2B scenario, there is a higher level of digital engagement between enterprises and the consumer.

Highlighting the difference between the erstwhile diagnostic analytics and the current predictive analytics, a report2 from marketing consultancy firm e-Consultancy says, “With predictive analytics, we are still relying on data from past events, but instead of using the data to describe or explain the past, predictive analytics uses data to get more data… to help us make better decisions. One of the most apparent differences between predictive analytics and descriptive analytics is that its output is data to be used, not just read.”

Predictive analytics boosts predictive marketing

In fact, predictive marketing is going be one of the biggest uses of predictive analytics in the coming years. According to Zion Market Research’s report3, the global predictive analytics market is expected to reach approximately USD 7.8 billion by 2020, growing at a CAGR of around 17% between 2015 and 2020. Key areas where predictive analytics will be used include customer and channel insights, sales and marketing, and finance and risk. The Zion report anticipates the marketing segment to emerge as the biggest user of predictive analytics with cross-selling, campaign management, budgeting and forecasting models in the coming years. The use of predictive analytics in marketing strategy is soon going to be the de-facto practice, and will be as important in B2B business as in B2C.

  • Try to apply predictive analytics and machine learning at every step of the customer lifecycle.
  • With predictive analytics in place you will be able to anticipate the business moments when your target audience is most likely to pay attention to your product or solution.
  • You can focus on the individual with informed messaging that enhances the customer’s buying journey, and creates a strong brand relationship.
  • The key to successful predictive marketing is when you are able to deliver a tailored customer experience both during pre and post-sale.
  • Use predictive analytics to understand the need even before the customer expresses it.

Reference:

[1] Gartner Business Intelligence & Analytics Summit 2016
[2] Analytics approaches every marketer should know #3:Predictive analytics
[3] Global Predictive Analytics Market Poised to Bring in $7.8 Billion by 2020

 

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