We are already well underway in 2017, Artificial intelligence has never shown such prowess that it does today.
Predictive analysis is one of the key outcomes of this surge and AI is in the middle of the whole deal. One of the key branches that came out from Predictive analysis is predictive marketing. Predictive marketing has changed how marketers and sellers approach a prospect customer or user.
What is Predictive Marketing?
Despite the buzz around predictive marketing, a lot of people still don’t understand the term whole-heartedly. People still find these complex terms as some sort of technology that their brand isn’t ready. Let’s end that today.
Our definition of Predictive marketing is:
Predictive Marketing is the process where an AI engine embarks on collecting data on consumers and potential customers (visitors) behavior, web-journey, and engagement. Based on the collected data, AI and machine learning deliver relevant optimization and recommendation on the fly. This automatically drives higher user engagement and boosts your conversion rate. It recommends marketers and sellers what actions are more likely to succeed and which are more likely to fail.
In simpler terms, Predictive marketing can help you achieve your targets faster and enables marketers and sellers to concentrate on things that truly matter.
Digital marketing is three-step process, which is, Attract, engage and sell. And, Predictive marketing helps you out with all the three steps. Let’s take a look at one of the best examples in the industry, Amazon.
Amazon has a very powerful AI engine that monitors all the users landing on their website. Once we have shown our interest towards a product, the engine starts interacting with us. If we bounce off the website without making the purchase or abandoning our cart, Amazon’s AI engine triggers a win back based conversion campaign. Later, we start getting targeted emails and advertisement about the same product, pushing us users to make the purchase. Thus, increasing the chances of completing the sales cycle.
Now let’s look at a few things that Predictive marketing can do and how it makes work easier for your marketing and sales team.
Things that Predictive Marketing is rapidly changing?
- The Marketing rule of 3Rs – Marketing is all about providing the 3Rs, right information to the right user at the right time. If these 3Rs are pointed out with higher accuracy and precision, the chances of a user preferring your brand over your competition are higher. For example, if a message is customized and triggered based on the customer’s behavior, there is a higher chance of converting the customer. This, in turn, increases your brand value and visibility among competitors. And, in the end, the brand with better visibility will always lead when it comes to closing a sale or tying a user with their system.
- Predictive Marketing cuts down capital burn rate – One of the flaws of our human nature is, we sometimes tend to work on our instincts and like to take these shot-in-the-dark approaches. This might lead to a lot of success but most of the time we end up wasting a lot of precious resources available to us. That’s not the case with AI and machine learning, as these technologies only take decisions and make amendments based on hard data. Therefore, decreasing the instances where you end burning capital or increasing the chances of garnering a low ROI on your investments towards marketing.
- Predictive Marketing bridges the gap between Sales and Marketing teams – Today a lot of brands face a similar issue, their marketing team and sales team have totally different views on common problems. The information that is gathered by AI, as said before, is based on hard data. The information gathered takes crucial data points into account like customer sales stage, their on-site behavior, last seen on website data, etc. Such a data set allows us to measure our efforts collectively and therefore both teams could work in sync based on things that worked and things that do not. Thus resulting in improved efficiency between the marketing and sales team efforts and helping them work towards a common goal, increased conversions.
- Increased user engagement based on User’s situation – One of the best part of an AI engine is the part, that could it virtually extract any sort of data necessary. Set down the rules and let AI take over. It could map the content and communication based on the user’s situation/stage with a brand, like, Stage in the conversion funnel, industry-vertical, prospect’s role in the firm, stages of sales cycle, geographic location, behavior and engagement habits, prime-time channels and more.
- Improving Emotional Connect with readers – Each person has their own approach and is often biased on how they approach a user’s based on their own emotional state. This results in an approach that becomes jarring in the long run. Whereas AI can make an effort based on every kind of interaction with a consumer, for instance, it can monitor if a user is facing a complex situation and recommend a solution to combat such situation. For example, if an AI engine looks at a user reading more about leadership skills, it could direct an approach where it serves the user more content about the very topic to win over the mindset of the user. This is one of the examples where the reader can emotionally connect with the brand and prefer it over its competitor.
- Optimization on the go – AI engines is the crux of predictive marketing. It is always analyzing and implementing optimization on the go. It enables you to spend less time on setting rules and targets for your marketing campaigns by being involved on its own with your existing infrastructure. For example, AI can concurrently make changes to your existing email campaigns by looking at the data points like CTOR rates, Open rates, user activity based on time, etc. Whereas if this task is to be handled by a user, it becomes tedious, as you’ll have to keep monitoring the data points over time and making manual amendments.
It is pretty evident that AI and predictive marketing is rapidly changing the landscape of marketing. Marketing has been around for ages and predictive marketing is the newest innovation in this space. We have a lot of case studies that argues the same for AI’s capabilities. It has helped us understand that there exists a gap between our marketing strategies. Now with the help of AI, we exactly know what has to be done and we have been arming our sales team with what they need to close deals. And what better than predictive marketing to bridge the gap between these two teams who have always be co-dependent on each other for their efforts.