Predictive Analytics for Marketing: What It Can Do and Why You Should Be Using It
Predictive intelligence is nothing new. In fact, for several years, businesses have used advanced analytics tools to detect fraud, assess risk, and even predict maintenance needs in airplanes to decrease flight delays.
However, understanding the results of predictive analysis and transforming data into insight hasn’t always been easy and typically required advanced skills. With limited computing capabilities and difficult to access, complicated software, predictive technologies never quite made it into mainstream marketing strategies.
Until now.
Today, artificial intelligence-powered (AI-powered) marketing tools — chatbots, content curators, dynamic pricing models, etc. — are both easy to access and affordable, creating opportunities for more businesses to reap the benefits of world-class analytics, even on a shoestring budget.
Powerful, advanced, predictive analytics are the “in thing,” and savvy marketers are not only looking back with the numbers, but also forward. Let’s explore predictive analytics for marketing — what it is, what it can do, and why you should be using it.
What Is Predictive Analytics for Marketing?
According to SAS, predictive analytics is “the use of data, statistical algorithms and machine learning techniques to identify the likelihood of future outcomes based on historical data. The goal is to go beyond knowing what has happened to providing a best assessment of what will happen in the future.”
Salesforce explains the marketing connection: “Predictive marketing uses data science to accurately predict which marketing actions and strategies are the most likely to succeed. In short, predictive intelligence drives marketing decisions.”
Sounds great. So, how can predictive analytics add more insight and clarity into your marketing decisions?
How Can Big Data Analytics Help Businesses Realize Value?
Businesses with an eye to the future realize that they want to know more than just what happened in the past; they want to use their data to predict the future. Predictive analysis makes current and historical data you already have more valuable by helping you better understand relationships to make more informed decisions.
Today, “91% of top marketers are either fully committed to or already implementing predictive marketing.” Here’s what they’re doing.
They’re Predicting Customer Behavior More Accurately. For marketers, customer intelligence is the name of the game. The more you understand your customers — what they want, when they want it, and how — the easier it is to reach them across channels with the right messaging at the right time.
Using predictive techniques guided by machine learning and artificial intelligence, predictive modeling helps assess future customer behaviors by identifying patterns and similarities between variables in the data. For instance, regression analysis identifies correlations between customers’ past purchasing behaviors to determine the probability of future purchases.
Predictive models can also help root out dissatisfied customers you’re in danger of losing as well as identify excited customers who may be ready to buy. Running customer data through predictive models can help you better anticipate behavior to better inform marketing strategy.
They’re Identifying and Prioritizing Qualified Leads. Unqualified leads — those with no inclination to buy — end up costing companies time and money. With predictive analytics, an algorithm helps qualify leads by prioritizing known prospects and accounts based on their likelihood of taking action. Identification models find prospects who have similarities with existing buyers, maximizing opportunities for new sales.
Even better, insights from predictive analysis can help your sales team concentrate on and nurture your most profitable customers. Find prospects who show the most potential, and you give your sales teams valuable insights into who to talk to next and which prospects will be most likely to close a deal.
If your business has limited funds, predictive analytics is a powerful tool to help ensure the right resources are used at the right time while forecasting high-value customers with the highest probability of buying for optimized marketing spend.
They’re Nailing Personalized Messaging. Personalization matters. Yet, brands struggle when it comes to providing their customers with customized messaging. Either they don’t have accurate data, they don’t have enough data, or they simply can’t gain insights quickly enough.
For others, the payoff for personalization done well is an extraordinary customer experience that exceeds expectations. However, the manual approach to personalization is unsustainable, and businesses are turning to machine learning and predictive technologies as the next logical step.
Predictive analytics drives automated segmentation for personalized messaging, meaning you can better target specific groups or individuals when you upsell, cross-sell, or recommend products, reaching customers with unique messaging that resonates in real time.
Why Should Predictive Analytics Matter to You?
Today, data is the new oil, and businesses are “spending an estimated $36 billion on storage and infrastructure” — a number that is expected to double by 2020. With more data, improved computing capabilities, and easy access to vendor tools, predictive analytics for marketing is not just smart — it’s a business imperative!
Predictive models can forecast marketing performance based on past campaigns, uncovering opportunities to improve so you can better understand your customers’ behaviors, deliver more meaningful content, and create customized experiences that wow.
The good news? Deploying a predictive analytics solution is neither complicated nor something that needs to be done solely in-house. In fact, tons of amazing solutions are available for both large and small companies — even for businesses that lack maturity when it comes to analytics.
Brian Byer, VP business development at Blue Fountain Media, has some wise words to share: “Using the right tools that will enable you to leverage data … is much easier than trying to reverse engineer a solution into a legacy tech stack. Plan to succeed and it will make incorporating predictive analytics and other new technologies much easier.”
In Sum
With the tech landscape changing rapidly, companies that succeed will empower their teams to use tech-first solutions to better serve their customers. They’ll embrace new tools, avoid analysis paralysis when adopting new technologies, and plan for change as a new opportunity. The agile approach to business is future-focused and a must for success in 2019 and beyond.
Accurate and timely business intelligence will be a differentiator going forward. While there are many reasons for using predictive analytics, the most persuasive is also the simplest: go beyond learning what happened and why to discovering insights about the future, and you’ll better serve your customers today.
