There is an increasing buzz around predictive analytics for marketing and sales success.

Although it might sound complex, predictive analytics is simply the practice of extracting information from existing data sets in order to determine patterns and predict future outcomes and trends. Or put another way, it’s about looking at the past to try and discern the future.

You will have encountered predictive analytics if you have ever phoned a contact centre for customer service or a sales conversation. In this scenario, a script is suggested to the contact centre agent based on predictive analytics applied to your customer profile (which products have you bought, what is your income bracket, what is your lifetime customer value, and so on). Predictive analytics takes this information and quickly works out what the likely outcome will be. A prescriptive recommendation is made using predictive analytics as to what the best next step for the agent to take would be for an optimal business outcome.

Predictive analytics for content marketing

Now this same predictive and prescriptive capability is extending into the world of content marketing.

Predictive analytics tools like Content Intelligence enable organisations to solve various problems by analysing the content that prospects and customers are reading, and using that to inform marketers, salespeople and demand generation execs what to write, send or say next.

Predictive analytics can be applied to various content marketing problems, including:

· Content wastage

It’s an uncomfortable truth that there is an appalling amount of wasted content that remains unused in the enterprise environment. The amount varies – former SAP executive Michael Brenner found it to be 60%, whilst Corporate Visions have suggested it’s as much as 90% – but effect it still the same.

Predictive analytics will identify the pieces of content that will be most engaging to your prospects and customers, and make recommendations as to which pieces you should send to them. This saves salesperson the time of having to wade through a central database and having to learn about all the content that is available at their disposal.

· Leaky funnel

No matter how good your demand generation is at bringing in MQLs – it’s hugely difficult to maintain their interest throughout the buyer journey. All of us suffer from a ‘leaky funnel’, or what we’ve termed interest abandonment. Leads will go cold or opt-out before they make it to a first, second or third meeting. It’s harder still to know what content to use to reactivate cold leads.

Predictive analytics can identify leads that are likely to churn and take action using your content. One example of this is personalization: rather than uniformly showing visitors to your site the same content each time, predictive analytics will examine each visitor’s content consumption history and display the most engaging content to retain their interest.

· Improve Marketing-to-Sales handover

The Marketing-to-Sales lead handover is a crucial point in lead management. It’s also the site where most revenue is lost – for a variety of reasons. Predictive analytics solves a variety of issues during the lead handover point, not least because it enables salespeople to prioritise leads. Predictive analytics also enables marketers to pass on a large amount of lead intelligence (such as their emerging needs and interests) to salespeople for a more informed sales discussion.

Learn more about predictive analytics

Marketers are used to using analytics to tell them what is or what has happened. Now we want to look forward with predictive data, not just sort through what happened yesterday. We want something that can help predict content marketing success – fortunately, that is now a reality.


By Andrew Davies, co-founder and CMO of idio.

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