Why Product Should Own Your Customers' Business Objectives

Shachar Avrahami at UXDX Community: Owning Customer Success & Shaping the Web’s Future. Video: https://youtu.be/8UWBbPTVUxI

Readable transcript: edited from the recording's captions for readability (fillers and false starts removed, punctuation and section headings added). Wording is the speaker's own. Timestamps are positions in the video. Names marked [?] could not be verified against the audio.

Emma meets a new platform

[00:00:07] Hey everyone. Thank you for having me here today. As mentioned, I'm going to speak about why product, or the product department, should own, at least partly, your customers' business objectives. Just a little bit about myself. I started my tech journey in the customer success domain, specifically in customer success operations and revenue operations. I worked with customer-facing teams to make them more efficient and more organized. For the past five years I've been the VP of Product and Strategy at EverAfter. In my personal life, I have a really, really cute cat. I'm sure that you're smiling when you see this picture, but unfortunately I'm not able to see that.

[00:00:55] One slide about EverAfter. We are a B2B customer interface platform, and we allow B2B organizations to productize a whole bunch of different customer programs, to make sure that customers achieve their desired outcome with your solution.

[00:01:15] Let's start. I would like to start with an analogy that I had when I saw the movie Inside Out. I don't know how many of you actually saw it, but Inside Out is a really great movie by Pixar that takes us into what happens inside the main character's mind. They have a lot of different emotions, and each emotion has a different role. I saw this movie a few months ago with my nephews. I promised them that I would do a movie day with them, and I forgot, and then my sister reminded me. So we watched this movie, and when I saw it, it sparked some ideas on how we could apply some of the things that they show in this movie to what we do when we build really great products and workflows for our customers.

[00:02:09] I'm big on AI, so I definitely use a lot of AI pictures in my presentation. I would like to first introduce you to Emma. Emma is a made-up character, a marketing operations manager at a 500-person company. She's a top performer in her company, and now her manager would like to introduce her to a new technology that he wants her to implement. Let's say that this technology is a made-up company called Funnel Pro, and Funnel Pro helps marketing teams solve a lot of their challenges. Because Funnel Pro is a platform, Emma realizes that the platform has a lot to offer, which makes it very difficult for her to start.

[00:03:02] When she starts, and I'm sure that you're all familiar with this, she gets an email with a lot of different resources that she should use, she should read, she should watch. She got this automated email: "Welcome to Funnel Pro. Here are your 20 different resources." It was a bit overwhelming for her. The struggle is real, because how could you even start when you have so many things on your plate? How could you know what would be the best path for you to succeed? So she tried to speak with someone. She opened a support chat, and she got a reply from a CSM, a customer success manager, who was able to meet her only five days later. And with that, Emma was a bit stuck.

[00:03:45] We are going to fix the situation that Emma experienced towards the end of this presentation. But I'm sure that many of you who have been introduced to new technology might have experienced the same sense of being a bit overwhelmed.

Why customer success became the personalization layer

[00:04:02] As I mentioned, I come from a customer success background. I made the transition to product, and I'm building products in order to solve a lot of the customer success challenges. I don't know if you're familiar, but customer success is one of the fastest-growing departments of the last decade. You can see that in the number of new positions in this area, and in customer success's share of your companies' headcount. While this is a fact, I do want to zoom in and understand why the demand for customer success is so high.

[00:04:44] Based on what I know, this is the number one reason that customers need a customer success manager, and I'm going to connect it to product in a minute, because it actually starts with our products. The products that we build became more complex. We no longer offer point solutions; we have platforms. It's no longer one size fits all. We try to serve different personas across different industries, and therefore we have different goals to solve for. We have different integrations, we have different workflows. We build much more flexible platforms, which means that we have many more configurations that our audience needs to learn, and that creates a challenge.

[00:05:26] And not only that: our customers, and I don't know how many of you would agree, also became more complicated. Now they have more stakeholders to whom they need to prove value with the product that they chose. They have a lot of legacy systems that they need to integrate with the new tech that they just purchased. They already have their own workflows. They have a lot of regulations they need to follow, GDPR, security, permissions, and a lot of different challenges, which makes every implementation, and any work with an existing or a new platform, a bit more challenging.

[00:06:09] When we combine the complexity that we build into our sophisticated products with the natural complexity of our customers' organizations, it's very difficult to succeed without doing anything in particular. Basically, in order for our customers to succeed, we need to come up with a personalization layer that will help guide customers and create for each customer their own personalized path to success. When we build this personalization layer, there are a lot of different factors that we need to take into consideration: the products that our customer purchased, the roles of the people that we work with, whether it's a big customer or a small customer, which tech they need to integrate. A lot of different parameters. That basically means that every customer has a different path to success.

[00:07:06] We as an organization, and in a moment I will speak about our role in product for that, really need to create this personalization layer for our customers. Throughout the years, the personalization layer that the industry came up with was the customer success manager. The customer success manager is the ultimate personalization layer for your customers. If we zoom into the mind of a top customer success manager, basically they create an algorithm with a lot of different signals that they know about their customer, because they know the customer best. They know their goals, they know how they use the product, they know the industry, they know the segment, they know all of the changes with the stakeholders, they know the health score.

[00:08:01] So they have a lot of different signals that they capture throughout their work with their customers, and the top ones basically inject all of those variables and signals into something like an algorithm. Obviously it's not a real algorithm, but their mind acts as their algorithm. They try to cross-analyze all of those signals. They try to really understand what is urgent and what is impactful. A great customer success manager will know how to curate for the customer, with all of the things that I just mentioned, the most valuable action that the customer needs to take. This is basically how they are able to drive success and create this layer of personalization for the customer.

[00:08:50] It could be that they tell the customer, "You need to use this feature, and this is how; you need to watch this recording or this video." They could build a success plan together with them. And to be honest, when the customer success manager provides relevant and personalized guidance and recommendations to the customer, I would argue that in a different world, or with a different mindset, that should be our role in product, because our responsibility is to make sure that our customers have a really good path to success.

What breaks when product doesn't own customer outcomes

[00:09:27] The title of my presentation was why product should own your customers' business objectives, so I want to give you some examples of what happens when we don't own our customer outcomes. In general, when large organizations purchase our software, our platforms, our solutions, they have specific outcomes that they expect to have with our platform, and as our platforms mature, we can assume what those outcomes would be. However, it has become a reality that the person or department that owns the customer outcomes is customer success. And I'm here to challenge that, because I think that in our own product departments we have a lot to gain, and a lot to lose, if we don't think about how to own the customer outcomes.

[00:10:27] Let's start to talk about that. First of all, when we don't own our customer outcomes, the feedback loop that is so valuable for making sure that we develop the right stuff breaks, because we need to rely on other departments to provide us the feedback. We don't really hear it firsthand, and we don't really witness the challenges that our customer success managers face when they try to work with customers towards the right outcomes. This means we might build the wrong things, because we don't build the things that would move the needle towards achieving customer outcomes.

[00:11:05] When we optimize for adoption of specific features, or time spent in our app, we might forget that even if our customers have high usage, it doesn't mean that they will necessarily retain or stay with us. So there is a chance of a higher churn rate when our customers don't meet their outcomes. I think that this is a challenge that we have to face, and we have to see how we can optimize and help the organization solve it.

[00:11:38] That leads to customer success and sales having to fill the gap for us, because we build a super sophisticated platform, and in order to use it, someone needs to really digest it and someone needs to create a path for our customers. So they fill the gap for us, which is not optimal, because they have other priorities to focus on. And I think this leads to us becoming a service function and not a strategy function, because we will rely on sales and on customer success to tell us what our customers need so that we know what to develop.

[00:12:16] I think that now, especially in 2025 with the rise of AI, we suddenly have a choice to get closer to really helping our customers achieve their outcomes. Until this point, in order to create this personalization layer, we relied on customer success managers. Now, in today's world, the new world, we have the ability to develop this personalization layer so that it relies more on technology and less on our customer success managers. And if we do it properly, then this technology, and it's not a specific tool or a specific platform, it's the thinking behind it, uses technology to help us curate the next best action for our customers, to make them more autonomous so they can achieve their desired business outcomes.

The autonomous customer org

[00:13:17] For that, I would like to introduce you to a concept called the autonomous customer org. The autonomous customer org is a concept that we came up with, and basically, when we are able to roll out this autonomous customer org, our customers and we in our organizations have a lot to gain. The autonomous customer org, which I believe we should own in the way that we build our product, is a system that pushes customers towards never-ending progress. We design a system that will fit each customer with an adaptive path in-app, inside our product, that will guide them based on their input and based on the signals.

[00:14:15] I'm not talking about tooltips or in-app tours. I'm talking about an actual system that will be part of our product, that will listen to the customer, that will ask customers what they need in order to succeed, and will be able to focus the customer on the actions with the highest impact, based on everything that we know about them. This autonomous customer org system will speak to the customer in their own language. It will know how they like to learn and how they like to do things, and it will adapt based on that. It will focus the customer on getting things done, because when our customers do more, it gets them a bit closer to achieving their own business outcome. However, it will know to escalate to the relevant team members when needed.

[00:15:09] I'm going to share a framework for how I believe we can start building this autonomous customer org, and after that I'm going to show you four live examples of how you could build it tomorrow. The engine that we need in order to create this autonomous customer org, or this autonomous journey engine, contains four parts. The first part is the different inputs that we need to start gathering in order to make decisions. I'm sure that many of you track a lot of different product usage. Basically we need to create for each customer a data layer that takes into consideration a lot of different signals: product usage; the customer's goals, captured in a way that makes sense; the customer's lifecycle stage; who we work with, because two different personas in the same organization might have different goals, so we might need to help them become autonomous in different ways.

[00:16:16] Then, I don't know how many of you are familiar with the concept of next best action, but the next best action is a super critical part of making customers more autonomous. This is the big brain of the engine. It's a decision layer that takes all of the inputs and calculates for each customer the single step they need to take in order to maximize their desired outcomes. We borrow this model from marketing and from sales. There are a lot of studies that say that when marketing people incorporate next best action as part of the cart on an e-commerce website, it increases the cart size and a lot of really good things that marketing teams can benefit from. So we can borrow that when we build and design products, and incorporate into our product this next best action mechanism that will identify what the customer needs to do, in a very autonomous way.

[00:17:26] Then we also need to focus on how we surface this next best action to the customer. We need to tell them what to do, and why they need to do it, because when we give them a good reason, it increases the chances of them actually doing it. We also need to give them clear, embedded instructions on how to do it. And we need to surface the action in a designated interface, so you might have an area inside your product for next best actions, where customers can always go back and see the most relevant recommendations for them, and how we actually push them towards done.

[00:18:07] The last part is a feedback loop, where the system learns from the failures and successes of this particular customer, and of other customers with similar next best actions. Basically, we need to learn what went well, which actions got the most completion, and all of that.

Rewriting Emma's story

[00:18:26] So I'm going back to Emma, and I would like to rewrite Emma's story. As a reminder, Emma just got introduced to Funnel Pro. But the Funnel Pro product team really wants to make Emma autonomous, so they created these kinds of creatures inside Funnel Pro. The purpose of the creatures is to analyze everything that Emma needs. They will learn what Emma needs, what her challenges are, what she needs to focus on. They will blend it all together, and every time they will extract a single next best action for Emma. When the next best action is ready, they will deliver it to her in a super engaging way, and they will guide her until the action is done. They are always working on calculating the next best action for Emma, and they deliver it in a very engaging way.

Four ways to start

[00:19:41] If you're here with me until this point and you're curious about how to start the journey of making our customers a bit more autonomous, I would like to offer you four different options, and then another asset that will help you if you would like to see a full list of, I think, 15 recommendations. The most important thing for me, if you only choose one thing, would be to build an NBA, or next best action, mechanism. Luckily, today with AI, you can actually build an AI agent that will read all of the relevant data points for each customer and calculate the next best action for each customer.

[00:20:23] We actually use our platform for that. We have an agent builder, so we can generate specific next best actions, or we can train different agents on what we want. It's pretty small here, but I actually created a next best action agent. I pulled a lot of different data points on each customer, and every day this agent calculates, based on a lot of different data, what the customer needs to do. So it is able to curate the next best action for a customer. But also, because I really like visuals, I chose for the next best action to be presented every day as a pop-up to the customer, kind of like a Netflix recommendation. So every day a new image will be generated with AI, based on the agent that I built. With that, our customers have a really clear path for how they can progress in a meaningful way.

[00:21:25] I don't know how many of you are familiar with the concept of a success plan. A success plan is something that a lot of customer success managers do manually together with their customers, but we can actually build an autonomous success plan system. I'm going to show you an example that Okta was able to implement for their thousands of non-managed customers. Their framework, which is embedded as part of the Okta experience, takes customers through four different steps. The first step is to collect customer goals, based on what the product team knows customers are mostly interested in solving with Okta. Based on that, and on a lot of data about the customer's setup and product configurations, they calculate a maturity score for each customer.

[00:22:15] Right after that, they curate a list of personalized recommendations that the customer should take in order to achieve their actual desired business objectives. It knows what the customer did or didn't do, and it shows only the things that the customer didn't do that would help them achieve their outcomes. Once the customer completes 80% of the recommendations, they reveal advanced steps. As I mentioned, this is a process that could be done manually by the customer success manager, but many of your customers, and many Okta customers, don't have a dedicated customer success manager. So with this they are able to push customers to action in a very self-service way.

[00:23:07] Another approach, and here I'm going to show you something live from our product. This is, for example, the homepage that our customers see. When they click this little EverAfter sign, they get something that we've built and embedded for each customer. We give them a benchmark and a score on how they could use more capabilities from our platform. For example, each customer can see their score, and this is interactive, under Journeys, which is one of our modules. They can click here and see a deeper level of benchmarking, and for whatever is not green, they see clear recommendations of what they need to do in order to improve their score. This is calculated from our own product data on our customers on a daily basis.

[00:23:58] So every day we calculate and show them what they need to do, and we invite them to collaborate with us. We bring them the resources, and they are able to track the different use cases that they would like. What we saw once we did this is that it gives me, for every new feature or new module that we roll out, the ability to really push it and give some kind of score and guidance to our customers.

[00:24:28] The last thing that I would share is that you can also ask customers in-app when is a good time for them to act, and you can create an agent that will take whenever they like to learn. For example, my customers are free on Fridays at 2 p.m., so every Friday I will automatically block something in my customer's calendar with clear recommendations of what they need to do in that time slot.

[00:24:59] I know that this was a lot. I created a guide, and you can scan this QR code, on how to build an autonomous customer org. It has, I think, around 15 recommendations on how to get started. If you'd like to continue the conversation, find me on LinkedIn. I'm really happy to have conversations and help product departments start the journey. The most important thing for me to end my session with is this: I know that it sounds like a customer success mission, but I really think that in order to be strategic, and to really help build the right product, it's something that we should try to have more ownership of. Thank you. If you have any questions, I'm happy to answer.

Q&A

[00:25:55] Host: Excellent. Thank you very much, Shachar. I love the concept of personalization for recommendations, because you try your best to build one platform that fits all, and it can be very difficult depending on the needs of different customers.

[00:26:09] Shachar: Yeah. And it's a good challenge. We build robust platforms, but now we need to really provide a clear path for each customer to navigate this complex system.

[00:26:19] Host: Great. We have time probably for one, maybe two questions. I'll jump in with a question about the bit that I found the most difficult when I've implemented systems like this, and it's gathering the data around the org. As you said, there's that wealth of data, but in my experience it's often scattered around an organization. It's not in one nice, neat system that I can just extract it from. Do you have any recommendations or advice for people who might be looking to start on this journey about how they can start pulling that data together?

[00:26:57] Shachar: There is behavioral data, but there is also input that we can simply ask customers for. A lot of information will actually sit in your CRM. What we did was connect some of the fields that we have from the CRM and put them here in front of the customer, and then we asked the customer, "Hey, tell us what your goals are, and who we should work with to achieve those goals." By letting customers provide these goals, first of all, we are able to push them back to the CRM, so everyone in the organization can benefit from this data point, and we give the customer the ability to really tell us what's on their plate.

[00:27:40] So just ask the customer, and if it's part of a very engaging experience, in-app, they don't need to go anywhere else. That would be a good way to start. If you have a system that can track product usage, we use FullStory, for example, so we can track some of our product usage. We also use BigQuery, and we surface there when customers activated specific integrations and how many programs they have with us. So I think we can always start with something, even if it's not super holistic: start with something with customers and track it over time.

[00:28:27] Host: Brilliant, that's great advice. I love the mixing of the qualitative and the quantitative data there between your different systems. That actually brings us to time, so I just want to thank you once again, Shachar, for sharing, and I hope everyone out there enjoyed it as much as I did. Thank you.

[00:28:44] Shachar: Have a good one.