CMO playbook: How Pinterest uses data to create great customer experiences

Every marketer needs to understand how data and analytics can help create the right experiences for customers. A top practitioner from Pinterest shares his secrets for making investment decisions and driving positive outcomes for business and consumer users. This is a must-read for Chief Marketing Officers.
Written by Michael Krigsman, Contributor

Because customer experience is genuinely important, it has become one of the great buzzwords of our time. Along with stalwart mediaspeak terms like digital transformation and artificial intelligence, customer experience occupies a hallowed place in the modern jargon hall of fame.

Creating a great experience is dang hard because it demands that we rethink all the touchpoints and interactions a customer has with our company, brand, reputation, products, and services. Although we can control some of these interaction points - for example, the products we release - we can only influence other factors, such as brand reputation or how customers talk about us.

However, despite the difficulty, creating positive customer experiences is superlatively important for every business today.

For this reason, I invited a major customer experience practitioner to be a guest on episode 290 of the CXOTalk series of conversations with the world's top innovators.

Dutta Satadip is the Global Head of Customer Operations at Pinterest. His describes his mandate at Pinterest as, "bringing customers to the center of how we operate as a business." Before Pinterest, Dutta ran customer success for the Americas at Google.

During our in-depth conversation, Dutta explains his view of customer experience and describes his approach to investment and measurement with data.

Watch our entire conversation in the video embedded above and read the edited comments that follow. You can also see the complete transcript.

What is customer experience?

Dutta Satadip: Customer experience is effectively the sum of all the interactions that any customer or user has with the business. And, the reason I say it's all the touchpoints because it's not just when a customer calls for help, but it starts from the first time anybody engages with your business and the lifetime relationship they build with your business. It's not just transactional; it's a combination of transactions, summing all of them up, and the overall relationship that it builds together.

Traditionally, a lot of customer experience work has been around understanding customer satisfaction, understanding net promoter scores, and these are great, I would say, backward-looking indicators, scores, and measures of how customers engage with the business. These have been around customer service: I ask a question and I get a response, and how well I do in that.

When you combine experience and outcomes, that's customer success and customer operations. The big shift that we're all trying to work towards is, how do we, as businesses, understand these goals and put the customers in the middle of all of our business operations and how we execute internally?

In most organizations there are executives, there are functions, and each of the functions is incentivized to perform one or two things and do them well. Those types of incentives drive some version of either siloed organizations or siloed incentives.

That is why it is super hard to bring in the concept of the customer because, when we talk from the perspective of a customer, they honestly don't care whether marketing's goal is X and customer goal is Y. They want a seamless experience no matter who they touch, right from the start when somebody reached out to them to do something and ask them to invest in their company, in our case in the form of an advertising campaign, all the way down to when there is a billing issue, and somebody needs to resolve that.

Connecting the dots across different organization silos and the measurement and the metrics that go around that must evolve to become more cross-functional. That's the pivot that we are working towards.

How does Pinterest use data to create positive customer outcomes?

Dutta Satadip: It involves a lot of nitty-gritty, crazy amount of detailed work. These journeys are successful when we understand what the purpose is we are solving and what is the problem we want to solve. Trying to boil the ocean usually never ends up in the right position. Trying to select a technology platform before understanding the business problem typically does not end up in the right direction.

One of the challenges that we are working off at Pinterest is, how do we ensure we're a growing business? We have over 200 million active users on Pinterest. We want to grow these numbers. We want to make sure our advertisers and our pinners find value in the system.

As a newer platform, we've been a company only since 2010. We're acquiring a lot of new customers. Now, as we all know, to acquire new customers, our sales teams should be spending more and more time with customers. When we look internally, we see a lot of time being spent on internal activities versus on external activities. So, our goal is to have the best customer experience. But, if our sales teams are not really talking to customers, understanding their requirements, we are probably missing the mark somewhere. That's the basic, core problem we are trying to solve here.

What does that mean? For us, it means truly unpacking drivers of inefficiency in our system. We're now building that one view of the customer, all our customers' information, not only what they have spent with us and all the financial stuff, but also connecting that with all the issues, et cetera, that they have seen so far. How have we tried to work with them? How are our product adoption metrics looking?

Give a 360-degree view of that customer in one place because, if we've tried to solve that problem, now we have the foundation to go back and understand very different types of questions, specifically questions like, what kinds of services; what kinds of help can we provide to customers to maximize their outcomes?

For us, outcomes mean campaigns. Is it, giving them a better understanding of measurement? Is it, giving them a better understanding of their creatives, which is the image that shows up in the ad? Those are the types of conversations we want to build towards, but our first, and the foundational step is having a view of the customer in one place.

What is your framework for investment decisions around customer experience?

Dutta Satadip: That's a great question. When I joined Pinterest, even though I came from Google and had a similar business around online advertising, I spoke to everybody inside and outside the organization. I talked with about 40 to 50 sales team members to understand what they did with customers; why were customers buying from us; what were the friction points?

That gave me a very bottoms-up understanding of the challenges that are pertinent to Pinterest now for the business circumstances, conditions that we are in. Understanding that allowed me to stitch together the touchpoints that matter. Specifically, how are we working with our customers from start to finish?

We have effectively a few phases that we go through in our engagement interaction with our advertisers, number one. Are we doing some version of planning with our customers? Our customers know about us. They have expressed some interest. We're raising awareness, but we're doing some planning. We want to understand what they want to do.

Then, we want to do some version of a pitch. We construct a pitch. Our business is advertising. We get commitments on how much they would like to spend with us. Once we get that commitment, we go back and implement. Implement is our next phase.

Most advertising campaigns need optimization, tweaking, to make sure we are meeting the customer objectives. Optimization is the next phase.

We do some level of up-selling. We tell them, if they put some more money, they can get better outcomes. Maybe they can get more reach, or maybe they can get better conversions, which is people going to their website.

Last, but not the least, we want to package all of this stuff in the form of a nice measurement and give them synthesized outcomes, so we can have a discussion again, which is back to the plan phase and say, "Hey, we delivered this for you. What can we do more for you? How can we help your business grow?"

This process of going from plan, pitch, implement, optimize, upsell, measure, is the lifecycle that we came together after having these conversations internally and externally.

We look at, how do we want to operate, what does "good" look like, and what are the biggest friction points in each of them? Then, we can make a decision, "Hey, this is the place that has the biggest friction and, if you invest something here, this is going to give us the biggest bang for the buck."

Obviously, we are running numbers. Obviously, we are running models that are not always perfect, but that's the overall approach we are taking to prioritize our investment decisions.

Does data help you understand empathy toward customers in addition to more transactional measures?

Dutta Satadip: While there is technology to look at things like comments, scale, and do sentiment analysis, this is both an art and a science. Data is a good way to shorten the problem or refine or segment the problem. But, ultimately, there is obviously an element of understanding the business, having business intuition, leveraging our own experiences to layer on top of it.

Even for things like marketing outcomes, certain things we know to be true. We know there is a certain level of awareness that will drive product adoption. We need to do announcements and things like that for people to be aware of what we provide; what our value proposition is.

They are not necessarily a transaction. You can't take these events and say, "Did I immediately get X, Y, or Z?" They're not necessarily performance marketing objectives. They're probably more longer-term relational metrics that we are looking at.

We try to balance what is a more long-term needle we're trying to move versus what's a short-term thing we're trying to do. As an example, if you want to acquire more customers in a more performance marketing-oriented way, then the metrics are a lot more tied in and it's more metrics first versus if you're trying to build brand awareness, visibility, and relationship. It's a little bit more long-term.

You're trying to discern customer intent from the actions they're taking?

Dutta Satadip: That is absolutely right. On the platform, actions like pinning it onto a board, how many boards they have, all of those things are directional indicators of engagement for us from the pinner perspective.

Then, from the advertiser perspective, I always like to say money talks. If people love the outcomes of our campaigns, they spend more. If they don't like the outcomes, they shift budgets and they go elsewhere, right? We have a very clear sort of "voting" through a dollar system that kind of works on the advertising side.

When we look at what's happening on the pinner's side, when we look at what's happening on the advertising side, we can combine all of these perspectives. I really wish it was as easy as putting everything into a spreadsheet and just kind of sorting and picking the top two. The best we can do with data is we come to the top three, four, or five recommendations, and then we have discussions around what is the best outcome that we are trying to optimize for.

What kinds of data are you trying to aggregate right now?

Dutta Satadip: I see three big buckets.

One, there is an operational view of the data. Think about all the transactions, interactions. At the end of the day, things need to be tied in. Everybody is collecting them in their own silos. It's very hard to join the space of data. That's the foundational element of what we want to do, and that's what we're doing right now.

The second is the customer view of the data. Okay, we are doing these activities. Is it leading to better outcomes? I always say, "Just because I showed up, is that actually good or this was actually going to happen regardless?" We need to understand, through some statistical modeling, what correlation, what kind of services, what kind of interactions can be attributed to better outcomes. That's the second stage that we are working on.

The third stage is looking at a more business-centric view, around business decision-making.

But, the combination of understanding what's happening in the operations to how our customers are spending, what our win rates are, what our churn rates are, that's the big connection that we are working on building at this point in time.

With a platform like Pinterest, you have two very good measures/proxies. One is you click on it and you go somewhere. If it's working, we know somebody will click on it. The second one is, if somebody likes it, hopefully, they will pin it. Those are two very concrete actions in the system that we know, over a period of time, if we collect the data and correlate that, we will be able to give more concrete recommendations.

It's making these recommendations and making them extremely relevant when the customer needs it. It's combining; give them the right information, understanding where they are so that we can establish the right time to get that information. Those are the three pillars that we're trying to connect together at this point in time.

Can machine learning help Pinterest customers with aesthetic decisions?

Dutta Satadip: Machines can't really tell you if something is good or not good - not yet. I'm assuming that a technology is going to come at some point in time, but not yet. It can recognize patterns. It can tell you it's a banana or an apple, but it really can't talk about aesthetic attributes yet.

Then, what is beautiful to me is going to be very different than what is beautiful to someone else.

Beauty is in the eyes of the beholder, and that's what we are trying to suss out through data. If it is beautiful, what are you doing with it? That's either a click, a pin, or some kind of an engagement in the platform.

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