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February 14, 2023 (Updated: March 8, 2023)
No matter how much research you do or how well you plan your marketing strategy, there’s no guarantee it’ll be successful. After weeks or months of surveys, data mining, and developing documents, that’s not what anyone wants to hear. But it’s the truth. Predictive marketing could be your answer if you’re looking for a strategy that’s least likely to fail out of the gate. It’s not foolproof, but its roots in data and the use of AI and other tools can help make the results easier to count on.
Today, we’re looking at what predictive marketing is and how you can use it to put more faith in your content marketing strategy:
Predictive marketing is a strategy brands use that reviews a variety of company data to forecast the outcomes of marketing plans. Its results answer the hypothetical question of “what’s likely to happen” in your future campaigns. The concept has a history all the way back to the 1930s with the discovery of predictive analytics. That statistical process used data mining and machine learning to analyze current facts and make predictions about future and other unknown events. People mostly used these analytics to predict things like the weather or the lifespans of certain organisms.
In the 1990s, after the first big rise of the internet for commercial use, companies like Amazon and eBay began using predictive analytics to grow their companies. It became a widespread business tactic—called predictive marketing—in the early 2000s.
There are several advantages of using predictive marketing in your strategic planning. First, it helps you learn more about your target audience. By analyzing their behaviors, you can better understand how they interact with your brand and what they want from it. This helps you do better audience segmentation to target the right people, in the right ways, at the right time.
Predictive marketing also helps you better allocate your marketing budget and resources. By having an educated guess about what works best for meeting your audience where they’re at, you won’t waste precious time or resources on activities that don’t work. Other benefits of using predictive marketing include increased customer engagement, better customer loyalty, and increased company revenue.
Predictive marketing takes advantage of a variety of data sources to help you make educated guesses about your campaigns and other tactics. Some of these sources include:
Audience data gives you more background information about your leads and customers or clients. It can tell you how they browse your website, what content they interact with, and what factors push them to make contact or purchase from your brand. Many of your content marketing tools help you track audience behavior data. For example, your social media marketing dashboards often have information about the demographics and psychographics of your audience. They show engagement rates and other types of behavior metrics so you can better understand how people interact with your content.
Related: Using Psychographics for Audience Segmentation
Competitor data is any information you can find out about your direct and indirect business rivals. Your direct competitors are those companies that sell the same products and services you do to the same audience. Your indirect competitors are the ones you compete with for search traffic, which may not operate in your niche, but they do target the same keywords. The more you know about your competitors and how your audience interacts with them, the better you can understand what you’re up against when you market to your most qualified leads.
“CopyPress gives us the ability to work with more dealership groups. We are able to provide unique and fresh content for an ever growing customer base. We know that when we need an influx of content to keep our clients ahead of the game in the automotive landscape, CopyPress can handle these requests with ease.”
Director of SEO at Auto Revo
Customer purchase history is exactly what it sounds like: a record of everything each customer buys from your brand. It can include products, services, subscriptions, one-time offers, auto orders, and many other types of purchases. Knowing what your audience buys from your brand gives you a better idea of what they want or need. It can tell you if you need to get better at marketing some of your less-sold products or services. It can also help you see which of your more popular options may benefit from harder sells or more nuanced marketing on various channels.
Understanding your current leads and audience is helpful for predictive marketing. But if you don’t look at past consumer data around the industry, you’re missing a big chunk of your analytics. Predictive marketing looks at the present and past to make guesses for the future. If you’re not looking back at your old customer data or industry data to make comparisons, you’ll have less chance of understanding how processes and thought patterns evolve. Historical research can add context to numerical data to help anchor your predictions in a certain place or time.
Knowing how your website performs and how your audience interacts with it is a big part of predictive marketing. Whether it’s your blog, eCommerce store, or another area of your website where you push content and sales, you need to know how it appeals to your audience. If they find your website hard to navigate or use, that could impact your marketing and sales. Tracking metrics like bounce rates, page traffic, and other similar data can tell you more about your website and the relationship your audience has with it.
Related: Web Analytics: Your Complete Guide
Predictive marketing may sound like this elusive, fortune-telling type of process, but it’s actually something you see, and maybe even use, online or in the office every day. Here are a few examples of types of predictive marketing you can introduce to your strategies to better understand how campaigns and marketing efforts may perform:
Customer churn is the number of returning customers you lose after an initial purchase or partnership. Churn happens for a variety of reasons, but you want to stay on top of this metric because it actually costs your brand less to keep returning customers rather than constantly trying to appeal to new ones. Customer churn prevention tools and programs can help you analyze your current customer base for similar characteristics. It pulls from a variety of data sources to help you determine which customers are most likely to leave your brand, or worse, switch to a competitor.
When you figure out which customers are most likely to leave, you can then develop a targeted marketing strategy to get them to stay, lowering your churn rate. And even without fancy marketing tools, you can predict customer churn potential on your own, through channels like email marketing. Tracking your open rates, click-through rates, and unsubscribed can tell you who is most engaged with your email marketing and who might benefit from a new tactic, like a re-engagement email.
To become successful at email marketing you really need to know your audience inside and out. How often do they want to hear from you? What emails will they open? What entices them to click links within the emails? Even when you get a solid email marketing plan down, it can change in an instant with a change in human behavior. But that’s where predictive marketing comes in.
Your email marketing programs, like MailChimp, can track all the necessary email analytics like open and click-through rates or unsubscribes. We already talked about these metrics for tracking your newsletter for customer churn prevention, but you can use them for things like product suggestions or drip campaigns, too. By using the data, you can make your email marketing more personalized, which makes it more effective. You can increase your engagement and conversions to make email marketing a more worthwhile tool in your marketing toolbox.
Related: What Is Drip Marketing and How Can You Use It?
Attracting leads to your company is just the first step in a much longer process to take people from brand awareness to paying customers. You’re not done once someone makes the first contact with your website. In fact, studies show that someone has to interact with your brand an average of seven times before they take any kind of action to become a paying client or customer. But by seven interactions we don’t mean they’ll see your social media ad that many times and then hand over their credit card information.
Those seven interactions can come at different stages throughout the marketing funnel. That’s where predictive lead scoring comes in. Once you’ve collected a list of potential lead contacts, you want to continue to market to them to expose them to your brand over and over. But not every lead wants to receive marketing messages as often or on the same channels as others. By trying to market to all your leads 24/7, you’ll waste valuable time, budget, and other resources without a ton of results.
But with lead scoring, you can find your most qualified leads–the ones closest to the bottom of the marketing funnel–to determine how likely they are to make a purchase from your brand. Then you can prioritize how and when to market to each group based on where they fall in the funnel. Many marketing and analytics programs, like HubSpot, offer lead-tracking tools like this to help with the process.
Related: 13 Lead Generation Strategies You Can Start Using Today
Retail and eCommerce brands love using product suggestions to target new and returning brand customers. Here’s how they work. Let’s say a customer lands on your eCommerce page from a search engine because they want to see what types of record players your music store offers. They research two or three models, sign up for your email newsletter, and then click away from your website to browse Facebook. By taking advantage of retargeting strategies, that customer’s device remembers that they visited your website and looked at record players.
Your retargeting strategy may then suggest records and record players they should buy in sponsored posts on Facebook. It could also show them ads for your record players on other websites or send them product suggestions based on their browsing history in an email. The benefit of product suggestions is a more personalized browsing experience. People aren’t just seeing content suggestions for your team’s arbitrary picks of what to push. They’re looking at content based on their wants, needs, and previous search history.
Related: 12 Retargeting Platforms for Your Marketing Stack
Predictive SEO may be arguably the most tricky type of predictive marketing you can do, but also the most rewarding. Why is it tricky? Because Google and other search engines constantly update their algorithm and they don’t always tell you about it. How are you supposed to keep up with SEO changes when you don’t even know they’re happening? Engaging in predictive SEO can take away some of that guesswork, or at least prepare you for what could come. Most predictive SEO efforts focus on grabbing and maintaining high search engine positioning for your target content keywords.
It uses traffic and search ranking data to determine if your page or content is at risk of losing any visits or positioning in search. Many of your SEO marketing tools provide some form of predictive SEO based on your website content, competitor data, and audience behaviors. They may generate “at risk” spreadsheets to help you determine exactly which pages could lose their rank potential and by how much. If you find your pages are “at risk” you can then take steps to fix them so that it doesn’t happen. This preserves your search traffic and organic content reach.
Related: The Effect of Constant Algorithm Changes on Google
Though we’ve already discussed how you can use social media to share product suggestions, that’s just one of many types of predictive marketing you can do on these platforms. There are plenty of other “behind the scenes” predictions your team can make to get better reach, engagement, and other results from your posts. Social media management tools may help you decide which fonts or colors are most eye-catching for your followers. They can also give you predictions about the best time to share content or what types of ads to place on each platform.
The social media management tools use data collected from across your platforms to understand how your audience responds to content. They also let you take advantage of processes like A/B testing to gather more data about your audience and their behaviors.
Related: When To Post Content on Social Media
Though a helpful tactic for preparing for upcoming campaigns and industry changes, predictive marketing is still based on educated guesses. And a guess isn’t fact. Even if your marketing predictions are right 99% of the time, that’s still a 1% chance for error. No, predictive marketing isn’t always going to work and give you the outcome you want or expect. But that doesn’t mean it’s not worth your time. An educated guess is better than no plan at all.
Because predictive marketing relies a lot on human behavior, and humans can be nearly unpredictable at times, your best guess is truly good enough. The more predictive marketing you do, the better you can get at it. Predictive marketing is also good for contingency planning. Because the results aren’t set in stone, you can often run a few analyses or simulations to predict different marketing outcomes based on changes in your data and variables. Then you can be ready for multiple situations, no matter which outcome you encounter.
Predictive analytics and marketing have deep roots in automation and machine learning. With the sheer amount of data necessary to make accurate predictions, having a human sift through it all could take years. And nobody has that kind of time to wait to plan a marketing campaign. But just because predictive marketing relies heavily on things like AI to process data and predict outcomes doesn’t mean there’s no room for humans in the process.
Machines and AI are getting more sophisticated every day, but they’re still not humans. They can only do what they’re programmed to do. They can’t think outside the metaphorical box, as it is. You should always have a human quality assurance person check any machine-generated data and predictions for context. Does the data make sense for how you plan to use it? Is anything missing? While automation can save you time collecting and analyzing the data, only a human person can tell you if the predictions will truly work within your marketing strategies.
While the actual price point for predictive marketing is different for every company, it can get pricey, depending on what you want to predict. Some predictive marketing tools like Buffer, MailChimp, or HubSpot, may come with free trials. They may also have different plans and packages based on your audience and company size. If you only plan to do predictive marketing in certain areas, such as email marketing or social media marketing, this can cut down on the cost because you need fewer tools.
Unfortunately, the further your branch out into predictive marketing the more expensive it can get. That’s because you’ll be mining, collecting, storing, and analyzing more and more data. Even with AI and automation, the process takes time and oversight. If you’re thinking about starting predictive marketing, start small. Then you can scale your efforts up as your budget and sales increase.
No matter what type of predictive marketing you engage in, doing so can help you be better prepared for what’s to come with your audience and in your industry. The more you know, and the more educated guesses you take, the more solid your marketing plan will be. When you have a plan to guide you, it’s easier to make changes on the fly and adjust your marketing accordingly if things change midway through a campaign.