Radius, an up-and-coming SaaS company that specializes in predictive marketing software, collaborated with Forrester Consulting to produce this infographic on the impact of predictive analytics. First, let's go over the basics of predictive analytics.
What is predictive analytics?
Predictive analytics, applied to marketing, is the use of data and metrics to predict the most likely outcomes of marketing actions. Gartner defines it as:
"Any approach to data mining with four attributes:
An emphasis on prediction (rather than description, classification, or clustering)
Rapid analysis measured in hours or days (rather than the stereotypical months of data mining)
An emphasis on the business relevance of the resulting insights (no ivory tower analyses)
(increasingly) An emphasis on ease of use, thus making the tools accessible to business users."
More simply, Forrester defines it as "Techniques, tools, and technologies that use data to find models - models that can anticipate outcomes with a significant probability of accuracy."
Predictive analytics are important for any marketer or small business doing their own marketing. We can't properly market in the here and now if we ignore possible future outcomes of our decisions. We must consider potential impacts of each decision, or we might as well play blindfolded lawn darts to make major business decisions.
To truly take advantage of predictive analytics, you need to start with a good foundation: high quality data. You should be working with facts rather than "educated guesses" about your marketing, your sales, and your customers.
While the data needs to be concrete and reliable, your predictions based on that data will (obviously) not be as reliable. No one can see the future or truly predict the outcomes that WILL happen. We can only take a well-informed guess. To make the best guess possible, however, you need that great data foundation.
How are companies using predictive analytics to improve business?
Predictive analytics mesh well with inbound marketing tactics such as lead scoring, buyer personas, and the buyer's journey to use your marketing resources more efficiently. As the infographic states, B2B companies who utilize predictive analytics see 2.2x annual revenue growth and are twice as likely to exceed marketing goals.
Predictive Analytics for Business
Predictive analytics can be useful outside of the marketing realm - for instance, Visa is using predictive analytics to decrease gas pump fraud with lost/stolen credit cards.
Other industries, such as oil & gas and transportation, are using predictive analytics to reduce risks and manage assets. One rail company in the UK, Southern Rail, implemented TAPAS (Train Automatic Performance Analysis System) to analyze some reliability and operational issues. The data they collected informed their predictive analytics strategy, which ultimately doubled the reliability of Southern's Class 455 Fleet. This meant:
- Reducing delay minutes caused by congestion, unnecessary stoppages, and reduced traction
- Delays and cancellations reduced by over 60%
- Required maintenance reduced by 70%
- Poor performance fines reduced by over £1 million per year
As of 2010, Southern Rail was applying its predictive analytics to make its operators more efficient, drive more safely, consume less fuel, and optimize all aspects of business performance.
Predictive Analytics & Effective Online Marketing
Alison Murdock, VP of Marketing at 6sense, states, "it's possible to tap into the signals of the decision-makers and predict with more than 85% accuracy who is going to buy (both accounts and contacts), when they are going to buy, and what they are going to buy." Further, one 6sense client used predictive marketing to realize a 450x increase in conversions from MQLs to SQLs.
Mick Hollison of Inc. states, "Imagine the ability to accurately predict not only who your best leads and prospects will be, but when and how will be the most effective ways to reach them and then to engage."
That's the power of predictive analytics and predictive marketing.
Over 90% of survey respondents say predictive analytics helped them:
- understand how/why their best customers buy,
- identify new leads/customer opportunities, and
- optimize their marketing mix to reach the right buyers.
That sounds like a good deal to us. How about you?