Predictive analytics are by no means a new trend, though you may have heard more talk returning to the benefits of using them lately. Marketers and other business functions responsible for making plans based upon predictions extrapolated from past performance have been using predictive analytics for years.
Take a look at this definition from SAS:
“Predictive analytics combines techniques from statistics, data mining and machine learning to find meaning from large amounts of data. Whether you’re in marketing, compliance, customer service, operations or any other business unit, your data can show where you are – and predict where you’re going.”
The buzz more recently is because developments in analytics technology mean that we have access to more data now than ever before. We can cut to a more granular level, we can predict future behavior and we can use technology to create automated responses in line with those predictions.
According to a Forrester study, firms that use predictive analytics are 2.9 times more likely to report revenue growth at a rate that is higher than the industry average. Top-performing companies are also much more likely to be using predictive analytics than others.
There are some tremendous advantages for marketing departments who incorporate predictive analytics into their overall strategy — let’s take a look at some practical uses.
Build Better Customer Personas
Knowing who your customer is so that you can focus your marketing efforts is really marketing 101 these days. There’s no reason to be taking a “one size fits all” approach when there are so many options available to help you narrow down and find a target audience.
Predictive analytics takes creating customer personas to the next level. As Brian Kardon states in a Demand Gen Report article; “There are thousands of buying signals outside of what you are able to track within your marketing automation and CRM platforms. Predictive analytics can help uncover the right patterns of traits that indicate when a customer or prospect is most likely to buy or even uncover traits of prospects or customers with the greatest revenue potential.”
Predictive analytics can help marketers to uncover insights which they weren’t able to realize during initial persona research.
This brings up another valid point; you may have spent considerable time initially crafting buyer personas for your business, but these should not remain static. Predictive analytics helps you to add to them, to mold them over time as data provides you with more detail.
The IBM Big Data and Analytics Hub wrote a brief take recently on using advanced predictive analytics to create better buyer personas. A huge part of the power of using this analytics is that you can gain better insights into the unique context in which customers make buying decisions.
As they point out, the “every individual is unique” mentality has been somewhat drilled into people growing up over the past couple of decades, to the point where personalizing the experience they have with brands is becoming an expectation.
The challenge for companies is to be able to use the reams of individual data they gather to scale. Data points need to be integrated and scalable personas created using advanced analytics platforms.
Reach the Right Buyer (At the Right Time)
The huge advantage better-quality buyer personas give to brands is that more detail allows them to create well-tailored offers and messaging.
In fact, the whole idea of using predictive analytics in this way is that marketing can reach the right buyer at the right time with the right message.
“Likelihood to buy” is the golden opportunity which all marketers want to get a good handle on and, as this Hubspot article outlines, predictive analytics helps brands to predict that buying behavior so that they can make timely offers.
They use online pet care pharmacy PetCareRX as an example. Whereas PetCareRX used to take a “one-size-fits-all” approach with the same offers made to everyone depending on where they were at in their calendar, they moved to a more personalized model using predictive analytics to better understand and differentiate between customers.
The difference that making timely, relevant offers makes really showed up for them in their results. Quarterly sales increased by 38% and profit by 24%.
Of course, while the sale is the ultimate goal, it’s not the only one. Sales tend to happen when customers are engaged with the brand and can increase if they feel they are being looked after well. Predictive analytics can assist with lead nurturing by identifying the right moments to present customers with useful information, a whitepaper or quick guide on a problem they need to solve, for example. When used in conjunction with marketing automation tools, predictive analytics can be a powerful source for making data-informed decisions.
Predictive Lead Scoring
Lead scoring becomes particularly important for large organizations or those with rapidly growing lead lists. It gets to a point where it simply doesn’t make sense to contact all leads — you already know that some will be a waste of time.
Sales needs to prioritize their time based on contacting the leads who are the most likely fit, which is where lead scoring comes in. Lead scoring assigns a score to each lead based on factors which either qualify or disqualify them, so that those with higher lead scores are prioritized for contact.
Where do predictive analytics come in? Well, as Hubspot points out, predictive analytics takes over from traditional lead scoring methods because it employs an algorithm to determine factors which should be included and how much weighting to assign to each. Traditional methods involve marketing or sales determining factors and weighting with a much more manual process.
The beauty of predictive analytics here is that your software can learn automatically and make adjustments. It can note any information that customers who closed have in common, as well as for those who didn’t close.
Other Advantages for Marketing
The wealth of data which predictive analytics can provide helps marketers to see more angles on leads. Segmentation can become more sophisticated and marketing messages are given a laser focus. The roll on effect for marketing? Better campaign success and some real ownership over results.
With a general climate of greater accountability for marketing, justifying the marketing spend and being prepared to back it up well with data has become an expectation. Predictive analytics give marketers a more detailed view of where their customers are and how to focus marketing spend. Companies who are using predictive analytics to focus spending are often finding that they’re able to bring in more qualified leads for less overall spend because they’re able to remove a lot of guesswork.
In the Forrester survey mentioned earlier, 78% of respondents believe that the role of marketing has shifted from a predominant focus on demand generation. They believe the role really has expanded to include deal acceleration and more effectively engaging digitally with customers.
Predictive analytics feature as a top priority for marketers who are looking for effective tools to assist them in their expanded roles. This advanced analytics can help marketers to nurture the right leads and convert sales faster. They help give marketing a seat at the decision-making table.
Confident Marketing Strategy
The biggest advantage to a marketing strategy that predictive analytics offers is that it allows businesses to take action and develop future initiatives based on data. It’s not a hunch, a gut feeling, or a click your heels together three times and hope for the best sort of thing. You’re making decisions that are informed by data, statistics and past behaviors.
Marketing can take their seat at the table with confidence, knowing that they are able to narrow down a targeted audience and justify their distribution and spend.
Koombea can bring your data insights to life by creating app solutions your customers want. Contact us today to see how we can help you.