Friday, 17 March 2017

Michelle Huff of Act-On: Adaptive Journeys Leverage Machine Learning to Scale Personalization for Customers

No two customers are exactly alike. And that being the case, it’s highly unlikely their journeys to “customer-hood” are the same either.

As more channels and devices continue to proliferate, different people or companies will take several routes to becoming a customer. So it’s becoming more important everyday to find ways to make sure that path leads to your business.

That means having your organization ready to adapt early and often to changes in customer behavior. This makes it easy for them to move in your direction.

Michelle Huff, CMO of marketing automation platform Act-On, shares with us the idea of adaptive journeys, and how technology like machine learning and artificial intelligence can help you provide a more personalized pathway to engage individual customers and prospects at scale.

Here’s an recap of our conversation. To hear the full interview click on the embedded player below.

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Michelle Huff of Act-On: Adaptive Journeys Leverage Machine Learning to Scale Personalization for CustomersSmall Business Trends: Why don’t you give us a little bit of your personal background?

Michelle Huff: I’ve been in high tech for a long time and started off in marketing at a small company. Then headed to a mid-sized business selling website technology and content. Moved to, we were acquired by Oracle. I spent five years at Oracle, and then went to Salesforce, and so was actually there for four years. Ran marketing, product management, was their general manager before heading over to Act On here as their CMO. It’s been a fun journey.

Small Business Trends: Describe what you’re calling Adaptive Journeys, and how it compares to what we traditionally hear when we hear the term Customer Journey?

Michelle Huff: Thinking about marketing, we’ve always tried to find ways to make it personalized. We think in personas. We think about nurture tracks.

But I think as buyers, we don’t like stereotypes of people, but in some sense when we’re always kind of forced down these predefined paths. I know it feels like no matter what I do I always end up getting the same white paper. It feels like a stereotype from a buying standpoint. It’s a little frustrating when we hear from the company when they want something from us. The last interaction is when marketing thinks we’re done, right? We converted a lead to a customer. High five, we’re over, and we don’t come back until we’re trying to do an upsell program.

I think marketing has been trying to adapt, and think about how we make that journey with the customer more personalized, more authentic. How do we start engaging with them on the channels that they want to? We know, it’s hard to adapt to make it much more authentic, and adapt to these channels.

Looking at all those challenges, we were thinking how can machine learning help this? Because in some sense, trying to track and score and measure and connect all the different interactions and learn from it is hard by that scale. What we’re wanting to do is build this into marketing automation, so that as marketers, when we build out these journeys and when people interact with us, it can adapt and change to the message that they want. The message that’s right for them, at the time they’re ready to engage, and in the channel that they want.

Small Business Trends: How does all this wealth of information coming in from all these different channels and different perspectives, how does that help the modern marketer today connect and stay connected along that journey?

Michelle Huff: I think for me, when we think of artificial intelligence and insights, it needs to be actionable. It’s really hard when you just have to, as marketing, go to some separate place to be learning from stuff, off cycle. Then thinking about how you want to apply it. One that we’ve tried to think about is something really specific like when to send an email.

There’s the marketing thing of, “Do I send the email at nine AM on a Tuesday? Do I send it at 10 AM on a Wednesday? Often times we’ll put in, especially for marketing automation we’ll put in a few. Not just 10 AM at headquarters. It’s 10 AM in this specific timezone. While that’s great, if you think about how we come up with that decision, sometimes it’s literally just a thumb in the air. Finger in the air, “Let’s go for nine”.

We do have separate insights. We look at our past campaigns and we try to take a look at the open rates and see, “Guess what. Based on this we tend to get better open rates if we send it on this specific day of the week”. It takes a little time. You have to look. You also have to take some risk and try different days and times with other messages. But it’s ultimately always a little bit of a guesswork. It’s also an aggregate. No matter what, even if you pick nine AM because it’s a better open rate, there’s a lot of other people where maybe that’s not the optimal time, and you are kind of blanket applying that to everyone. It’s that stereotype again.

Where I think about the insights, it’s not just knowing, but how do we take that information and apply it into what we do, and an easy way for marketers to do. Even if the answer was available but you had to answer hundreds of questions in a week, and all of them required an analyst to sit down and review things for days, it’s not really practical.

How do we take that and actually go through, and in real time continue to learn and apply it, so that ultimately what marketing has to do is just pick a button and say, “Why don’t you just send this email when it’s the optimal engagement time for each unique person,” so when it goes out you might read yours at seven o’clock in the morning.

I’ve got two small kids. So I actually read a ton of my stuff at 10 or 11 o’clock at night.

As a marketer, I just had to pick a button, and for me, one day my kids will grow up. I might not stay to be a 10 or 11 o’clock person, and it might change. The nice thing is, artificial intelligence for all these insights will keep learning and adapting based on those changes.

Small Business Trends: How does this technology, and automated insights, change the relationship that marketing has with the sales folks?

Michelle Huff: How I’ve always thought of marketing and sales is that, even as a business leader, if you had the ideal way to interact with your customers you would want the best sales rep to be one-to-one interacting with every single one of your customers. They would be the ones who would remember their birthdays, just check in to see how they’re doing, read about an article and be like, “Based on this last conversation we had, I thought you might find this interesting”.

Once they become customers — “How’s it going?”– Just constantly interacting in a great way, and in a personalized way.

The challenge is, as we grow businesses, we can’t have a one to one rep for every customer we have. Marketing has really helped scale that relationship, especially as the journey’s disrupted and people start researching before they even reach out to anyone in the company. How do we make sure they have the right brand experience and provide the right set of information?

Once we get to know them, how do we remember them and say, “Based on this last thing you thought were interested in, I thought you might find this article interesting too.”

If we can find ways to have what we send out in marketing be more personalized and authentic, reaching out in the channel they prefer, when they’re most ready to engage. That really helps us align even closer with sales. Because it almost frees up their time in making their time the most optimal. It almost makes the partnership stronger.

Small Business Trends: How quickly do marketers have to get up to speed with this idea of adaptive journeys and leveraging the data and the machine learning, to have those nuggets delivered so that they can keep up?

Michelle Huff: It is a struggle. I feel like every time I talk to people in marketing we’re running. We’re trying to adapt. I guess how I’ve always thought about it is, it’s an evolution. If you look at social media, there’s still many people marketing who are still trying to figure out better ways to interact and engage with people in those channels.

One way that we’ve thought about adaptive journeys have been some of the journeys we see in our own personal lives with Google Maps and Waze and how you put in your destination, and based on knowing all these different points of data, where you’re at in your journey with your phone and your GPS, and layering in all these different data, it starts recommending and learning your frequent destinations. Your commuting hours. Your preferred routes. It’s going and doing all of that.

It’s providing this information, and from a marketing automation standpoint it’s going to be doing that too.

There’s still a lot of people I talk to in marketing that aren’t even using marketing automation. I feel like if you are wanting to take advantage of this, at least starting to think about, “How do I start putting in and thinking about the full customer lifecycle? How do I start putting in a lot of my assets and programs and putting them into systems so it’s starting to track and score and measure?”

Small Business Trends: With all this great technology folks like you and other companies put out that really improves the ability to understand what’s on the mind of customers in real time, are you surprised at the slow adoption of marketing automation technology?

Michelle Huff: I am. It’s interesting, It really depends on the industry too. We do see often times in high tech a lot of marketers, they take advantage of these types of technologies faster. There’s other types of industries where they’re just starting to. It does surprise me sometimes because I’ve been in high tech for a while and I’ve used it for a while. I keep thinking, “How do people survive?”. Because you can really do so much more.

But I do see a tipping point, and I do see more conversations, and people hearing about it.


This article, "Michelle Huff of Act-On: Adaptive Journeys Leverage Machine Learning to Scale Personalization for Customers" was first published on Small Business Trends

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