Predictive Analytics

Predictive Analytics: what every marketer needs to know…

Let’s start with ‘Big Data’. In theory at least, marketers in 2015 have it easy: we have the potential to access the type of knowledge about lead behaviour, motivations and expectations that our predecessors a couple of decades ago could only have dreamed of. From digital clicking behaviour through to social signals – as well as whole swathes of valuable data at your fingertips via your CRM and marketing automation tools, you should know more than ever about what drives your audience.

But how do you draw all of this together? What can you do with this raw data to transform it into valuable information that your business can put to work? Here’s where predictive analytics comes in…

Predictive analytics in a nutshell

In its widest sense, predictive analytics is about using mathematical modeling to draw together data from lots of different sources to make predictions about future events. For a marketer, this offers the potential to identify not just the best targets for a campaign, but also the most effective ways to reach out and engage with those targets.

Why should I take it seriously?

You can draw up more accurate buyer personas and genuinely useful content

The more you know about your target audience, the more accurately you can tailor your message. You can combine what you already know about your potential buyers with predictive analytics to reveal traits and patterns which otherwise you might miss. With this extra insight, you can go on to create marketing collateral that better addresses the needs of your audience.  

You can hone your lead scoring process

You probably already have a system in place for scoring leads – i.e. assessing the likelihood of a lead turning into a customer. On a basic level, this could just mean a tickbox exercise where you pass the lead over to sales if a certain number of criteria are met. Predictive lead scoring goes one step further and involves putting predictive analytics to work to rank and prioritise leads using statistical modeling tools. Does it work? Research last year from SiriusDecisions suggested that 90% of users agree that predictive lead scoring provides more value than traditional methods and 88% of respondents think such methods offer value for money.

You can get your priorities right

From time to time, your sales team will be faced with a backlog of sales-ready leads to make contact with. How do you prioritise who to call first? The answer, of course, is to focus initially on the ones that are most likely to convert. Speed is of the essence – with one study showing that the odds of making a successful contact with a lead are 100 times greater if the call comes within 5 minutes compared to situations where there is a 30 minute wait from the lead being submitted. When it comes to smart prioritisation, predictive analytics can come to your aid in the form of lead scoring that ranks leads in order of likelihood of conversion.   

So how do I start getting analytical?

Focus on the data first of all. Do you really know your customers? Can you track their progress from initial contact via your website through to contract signing and beyond? View this demo to find out how a full-feature marketing automation suite can help you capture everything you need to know about your leads and customers.

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