The Agile Path to Engagement: Solving the Personalization Challenge with AI

The depth of customer engagement depends, in large part, on how personalized the shopping experience is. If a customer feels like a brand knows them as an individual among thousands of other customers, they will purchase more from that brand, more often, and remain loyal.

The path to 1:1 marketing is paved with personalization, and while there are many personalization tools out on the market, it’s hard to understand which one(s) to pick. This can become particularly challenging when distracted by a shiny UI — though usability is, of course, vitally important to the marketing teams who desperately need personalization tools.

In this blog series, we’re going to take a closer look at some of the key elements that enable you to deliver personalized engagement that builds loyalty, while remaining agile enough to pivot on a moment’s notice. At the end of the series, you’ll have a better idea of what to be aware of when looking at martech so that you can understand the pros and cons of the various options, and make informed decisions in picking the kind of tools that will really do what you need them to do.

The Importance of AI

Unless you’ve been living under a rock, you’ve heard of AI, and by now, you should know that AI is actually something that makes your life as a marketer easier. Instead of adding another layer of “you can” to your overloaded day, it actually reduces your workload by handling tasks at a level that you couldn’t even dream of doing (that’s the joy of automation right there).

Now, is all AI equal? No. Does this mean that you need to become an expert in understanding the difference between Machine Learning and Recursive Neural Networks? No, but it does help to understand some of the basics so you can make an informed decision.

Data & Consistency

As a marketer you have to pivot rapidly and adapt to changes in customer behavior, and the data generated by these changes becomes your greatest personalization fuel.

“Data is the new oil” is something you’ve probably heard, and it’s true — but it carries a major potential downside: Someone has to process all this data to make it usable.

When you have to pull data from several point solutions, you’re going to get bogged down in transferring all that data to a place where you can use it — which means that you’re actually spending precious time on tasks where you’re not adding value.

If marketing software is focusing your time in the wrong place, i.e. data wrangling, instead of letting you easily launch and track campaigns, then your technology stack is costing you time and money.

One of the most valuable benefits you should find in a platform is the consistency it offers the marketing team, especially in the way data is gathered and interpreted. That uniformity is impossible when a human has to import data from a bunch of point solutions and crunch through it all.

But imagine how uniform a single Customer Data Platform (CDP) would make things. Campaigns would be easier to deploy (with industry-specific use cases already inside the platform to point you in the right direction for growth), and consistent reporting would allow you to adapt to changes in customer behavior faster. Your entire marketing team could work in one interface, access data in the same way, and optimize campaigns based on data insights.

Scaling Without Sacrificing Quality

So assuming you have all the data in place and you can just focus on execution, you still face the challenge of: The more channels and contacts you have, the less time you have to spend on tailoring content to each individual.

This is where you hit the human-limit of personalization scaling, because no matter how many marketers you hire, you will never be able to keep up with personalization expectations, let alone today’s speed of marketing to customers.

That’s where AI also needs to be involved, so that it can take care of setting up, launching, and analyzing campaign performance. A key part of using an AI-based customer engagement solution is making sure that it can identify trends based on the data. This will provide you as the marketer an overview to act on without having to spend hours interpreting first.

A Single Platform vs. Point Solutions

One of the really exciting changes in the marketing landscape has been the rise of point solutions — because they’re excellent at what they do, making them really tempting to use, as they offer plug-and-play results. The problem is that, in a larger ecosystem, they create silos of data and carry with them significant IT admin overhead, as there needs to be a way to try and coordinate the different activities and collate them into a single meaningful timeline per contact.

At the end of the day, consumers view your brand as a single entity — so it’s on you to make sure that they have a consistent experience across every touchpoint and channel. Doing so makes them valued as an individual. That’s why you need channel-agnostic AI that can actually deliver the same kind of experience as point solutions, but without the added complications of IT maintenance and admin overhead.

A single AI-powered platform is also easier for marketers to use than a dozen different solutions, because you’re just mastering the one tool instead of switching back and forth.

From a business perspective, it’s also cheaper and potentially more powerful than a plethora of point solutions. Raj Balasundaram, VP of AI at Emarsys, describes these vendor consolidation benefits:

“It is not only cheaper to use fewer vendors, but in the case of Emarsys, it’s a more comprehensive solution for your brand. You can do everything a marketer needs to do in one platform.”

Agile by Design

When looking at technology, a key factor to consider is your own independence.

Having a system that’s been hyper-optimised to deliver according to your marketing strategy is all very well and good — but what if you suddenly need to scrap those plans and start over at short notice? Being able to retool content and campaign automation on the fly is critical, which is why an overreliance on computer scientists, IT support, or even certain point solutions, can make future-you’s life very uncomfortable.

If your tech stack has the same kind of power as an ocean liner, then it’s worth noting that trying to turn or stop a ship of that size takes time and planning. As a lot of us are now painfully aware, time and planning are luxuries we don’t always have anymore — so you need to make sure that you have the kind of tools that let you roll out a campaign in just a couple of days without compromising on consistency.

Final Thoughts

Up to this point, we covered what AI is and how transformative it can be from the day-to-day perspective. We also discussed how it can let marketing teams punch above their weight by enabling much greater scalability (and ideally without the need for IT).

When you are thinking about tech, particularly AI, keep the following in mind:

Consistent — consistent and actionable data is the key to consistent customer experiences.
Scalable — factor in growth, but make sure that the brand experience doesn’t get diluted.
Futureproof — remember, long-term maintenance plus more technology equals more headaches. So keep it simple.
Agile — The world is speeding up, you need to keep up with consumers.

At the end of the day, you need a comprehensive marketing solution. With the right tech, AI can ultimately make marketers more agile and more insightful about what customers want from the brand. Being agile and able to move rapidly isn’t going to be helpful unless you know where you are going.

In the next post in this series, we’ll look at how marketing needs to be elevated and given a more strategic role within the business. We’ll touch on how valuable marketing-data insights can be for the organization as a whole, how marketing must play a much greater role in helping to guide the business to success, and how marketing can deliver the kind of outcomes brands need in order to thrive.