There are some things that you just can’t say without getting a deluge of questions in return. I’ve recently learned that the term “decisioning platform” is one of those things.
So what really is a decisioning platform? Who does it benefit? How are retailers using it today? And why is now the time to get running with one? Here’s what you need to know.
What is a Decisioning Platform?
When big data entered the scene, it presented numerous opportunities to deliver better results by bringing intelligence to decision-making. But it also presented two key challenges: How do you collect and store mass quantities of information and how do you put it all together in order to gain insight and prioritize the most important actions that drive business outcomes?
While we solved the first problem early on, most brands are still searching for a solution to the second problem as they continue to struggle with how to put all the data they now have to use.
Part of the reason we have yet to fully solve the second problem is that we don’t want to take just any action — we want to take the best action at that point in time. So how do you know if the action you’re taking is actually a good move to make? Without a decisioning platform, your odds are as similar as they are when playing “rock-paper-scissor” — you’ll win some and you’ll lose some, but you likely won’t beat your opponent every single time.
At this point, you’re likely thinking: What about marketing automation platforms? Don’t they help with customer engagement? They do, but only to an extent. These rules-based systems are valuable for taking immediate action when you’re dealing with one channel or a small data set, but if you want to prioritize actions across multiple touchpoints and real-time consumer behavior, you need a decisioning platform. We’ve reached a point where shopper behavior multiplied by the number of channels creates so much data that decisioning is not a human solvable problem anymore. As a result, we need to augment human decision-making capabilities with a decisioning platform that can ingest and analyze data to help users understand which actions to take and the order in which to take them to achieve desired outcomes.
Who Benefits from Using a Decisioning Platform?
A decisioning platform takes data insight and decision-making out of the hands of a select few data scientists and CRM gurus and puts it into the hands of a large portion of the retail workforce. By eliminating the need to rely on data science and CRM resources to determine factors like propensity scores, it empowers marketers to make decisions and take action faster than ever before.
There are three specific types of marketing users for whom this democratization of decision-making makes a big difference:
- Those who lead customer communication on a specific channel, such as email, social or display advertising (or any other channels that are in play)
- Those who manage customer systems of record, like a CRM or CDP, to better understand customers and determine their interests and preferences
- Those involved in data analytics and insights who try to predict things like short and long term behavior and customer lifetime value and try to understand how those factors affect business outcomes
How Can Retailers Use Decisioning Platforms Today?
Connecting offline and online experiences (and even online experiences across channels) has proven one of the biggest challenges for retailers over the past few years. We’ve now accepted that data is the solution, but I’d argue that it’s only a piece of the solution. All of the knowledge that data provides is a major step forward, but you still need to know what to do with that data. That’s where a decisioning platform can help.
For example, we now have all of these channels on which to engage customers, so how do you know which route to go? And how do you prioritize outreach across customers and channels? It’s an entirely new way to think about customer engagement, and it necessitates a new approach. A decisioning platform fills the gap by providing the support needed to develop something of an individual media plan for each customer based on their demonstrated preferences. It does this by pulling together data from disparate channels, using that combined view to inform the next best move to achieve certain outcomes (e.g. grow the lifetime value of customers) and allowing users to sync the results to any customer interaction channel to take action.
How does this decisioning look when put to work? Consider the case of one global athletic footwear and apparel retailer (who we can’t name publicly, but chances are you wear something of theirs each time you step on the treadmill) that wanted to identify new audiences to target across channels and improve cross-channel personalization. The retailer used a decisioning platform to guide these efforts and experienced a 76% increase in clicks on personalized content, a 30% increase in conversions on abandoned cart campaigns and a 130% increase in sales from Facebook ads as a result.
Why is Now the Time for a Decisioning Platform?
The combination of digital and the rise of Amazon have completely shaken up the retail industry. As brands chart the course forward, more and more are finding that the key to differentiation and customer value lies in their data and the ability to use it to create a 1:1 experience for customers. A decisioning platform is a critical component of that solution since it can provide the keys to unlock the insights contained in all of the big data retailers have spent years collecting and allow marketers to take action on it quickly.
In addition to paving the way for swift reactions, a decisioning platform also enables retailers to deliver more personalized, value-add experiences that help achieve business outcomes. Success in retail is not just about acquiring customers, it’s also about retaining them and growing their value over time. And to achieve those goals, you need to understand your customers and create personalized experiences for them. Providing this type of experience is more important now than ever in order to compete with the extremely high bar set by leaders like Amazon, Google and Facebook.
Finally, we continue to create more data at an increasingly rapid pace, and we’re on track to create about 1.7 megabytes of new information per person every second by 2020. That means we’ll be looking at a whole new set of possibilities and a new level of complexity in the years ahead. As a result, the need for a decisioning platform that can find opportunities and learnings in all of that complex data, quickly curate the best possible actions to take to achieve certain outcomes and allow marketers to execute on those recommendations with the click of a button will become even more apparent.