One of the biggest problems with many digital marketing articles, and we’re sure that you’ll agree, is that they assume prior knowledge. They assume that we’ve all been to university and spent many years studying for a marketing degree. What if you don’t have much experience? What if you’re a small business owner trying to manage marketing, sales, accounting, and every other department?
In recent times, you may have been confused about the terms ‘predictive marketing’ and ‘predictive targeting’. What do they mean? Today, we’re going to answer these questions in an accessible way for all. Hopefully, your confused look will transform into one of confidence and understanding by the end!
What’s Predictive Marketing?
In simple terms, predictive marketing describes the process of using data to help decision-making in marketing. By predicting the future success of marketing actions, we know where to focus our attention now. Data science considers the business and all information before then suggesting the marketing actions most likely to fail and succeed.
This is why so many marketers around the world are getting excited, just in case you’ve been wondering. While the definition of the phrase might sound simple, it’s when they dig deeper that some people get confused.
Before anything else, where does data originate? Here are some terms you might read in this niche:
Data Aggregators - Essentially, these are the entities that collect business data. This can include characteristics (firmographics), contact details, and more.
Data Enrichers - Next, we find those who enrich sales activity and marketing data. In turn, they provide insights for businesses.
Predictive Modelers - Finally, this group is all about mathematical algorithms (don’t worry, they take care of the mathematics so that we don’t have to!). By using algorithms, businesses can find patterns in data.
With the basic framework, the idea is that businesses move from one to the next as they scale and require more sophisticated systems. While most businesses start with data aggregation, they eventually progress to data enrichment and predictive modeling.
However, it’s important to note that this is just one model from Forrester. Gartner chooses to present this information differently and says that it can be broken down as follows:
Descriptive - what has happened?
Diagnostic - why did it happen?
Predictive - what will happen next?
Prescriptive - what shall we do about it?
Whether you subscribe to one of these models or even a different one, the aim is to go beyond learning what happened and why this event happened. These days, it’s possible to use this information to learn what will happen next and what businesses can do to prepare for it.
While you might think that predicting the future is about as advanced as it gets, you would be wrong because there is a way to take it even further. Some tools in the market have automation features so that businesses don’t even need to do anything to implement the changes. Once the insights are generated and the predictions made, it also takes charge of introducing any necessary changes.
How Does Predictive Marketing Work?
Although this isn’t surprising, everything starts with data. If the tool doesn’t have access to data, it has no way to assess the past nor can it predict the future. Naturally, when we talk about marketing tools predicting the future, we don’t mean that you’re about to win millions on the lottery. Instead, it predicts the actions of consumers so that businesses know what marketing tactics to use.
After collecting data from various sources, predictive marketing tools bring everything together alongside existing customer and business data. From here, it builds a clever predictive model tailored to your business. Rather than using a one-size-fits-all solution, these tools build special models given the data in question.
At this stage, the model is ready to predict the efficacy of specific marketing techniques and tactics. Since this is a guide for beginners, we don’t need to talk about the technology and systems running in the background. Instead, all you need to know is that the technology creates a model that assesses the viability of marketing techniques. Even when using a tool, you don’t need to understand what’s going on behind the scenes. Of course, this is something you can explore later.
So long as the vendor has access to your systems and data, it can build an algorithm and provide valuable insights in return. The only thing preventing you from succeeding at this stage is being able to use these insights properly. It’s one thing to get lots of valuable insights, but it counts for nothing if you don’t know how to use them.
When it comes to predictive targeting, the process works similarly, except the aim is to find the best audiences for a particular marketing campaign. Therefore, the tool will gather data, create a model, and assess the viability of targeting options before suggesting the best ones.
Predictive Marketing, Lead Scoring, and Data Science
One of the reasons why people get so confused in this niche is because many different terms seem to get used interchangeably. Mistakenly, people overuse phrases like predictive lead scoring, predictive marketing, data science, and predictive analytics. What’s the difference between all these terms?
When you use predictive technology to help your marketing strategy, this is known as predictive marketing. You’re using predictions to boost your communication channels, the buyer’s journey, and several other areas. To understand the term, it’s important to break it down into two:
You can’t have one without the other; the fact that you implement the insights into your marketing strategy makes it predictive marketing. On the other hand, predictive lead scoring aims to rank leads so that the sales team knows who to focus on first. The people at the top of the list are the ones most likely to convert, while the names at the bottom require more effort. While this is a form of predictive marketing, it’s not predictive marketing in and of itself.
The same is true for predictive lead generation, predictive segmentation, predictive targeting, predictive messaging, and predictive forecasting - these are all forms of predictive marketing.
Data science is a field that has grown exponentially in recent years. If we were to compare data science with predictive marketing, the difference would be the scalability with the latter. Many years ago, only businesses with huge budgets could even consider using data to help decisions. They would hire expensive data scientists and everyone else would look in their direction with envy.
Now, predictive marketing is used at scale as SaaS systems; even businesses that have only just entered the market can afford a solution. Not only are the solutions scalable, but they’re also based on the cloud. Both these factors remove the requirement for expensive infrastructure and in-house data scientists.
Integration in the Marketing Department
If you’re worried about integration, this doesn’t need to be a concern in 2021 since most tools are designed to work in a complex marketing system. With this in mind, you’ll integrate the predictive marketing tool with CRM and automation systems. The best way to integrate is to check your existing solutions to see if any of the providers have a predictive marketing tool. In the next section, we’re going to discover a company that has ad account protection, predictive marketing, and automatic ad optimization features.
As far as integration goes, the main reason for the feature is so that the predictive marketing tool can extract data. With the tool gathering lots of data, it can build the algorithm and help your marketing decisions in no time.
Potential Solutions
When shopping this market, you’ll see lots of valuable names including Everstring, 6sense, Infer, Fliptop, Mintigo, Lattice Engines, Radius, and more. Yet, there’s one that seems to rise above the rest and that’s Trapica. With this market intelligence tool, you’ll learn about customers, the brand, competitors, and more.
Once Trapica is linked with your system, it will analyze both search and social data to provide a better understanding of customers. Not only will you learn about them, but you’ll discover their behavior (and how these behaviors will change in the future!). Soon enough, you’ll receive more insights and context than you can even imagine.
Ultimately, this leads to stronger marketing decisions and better utilization of your budget. Since you know how behaviors will shift, you’ll know how to meet changing needs (before the competition even notices a change!). You’ll learn about the market, your audience, and even your ad campaigns. As you adjust targeting, watch as results improve.
Another reason why Trapica is such a strong solution is that it offers many other products whether you want ad account protection, ad optimization automation, or iOS 14 insights. Why not get started on the path of predictive marketing today? We hope this guide helped!