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Better Done Than Perfect · Season 3 · Episode 6

Email Automation Data & Integrations with Colin Nederkoorn

You'll learn about the common mistakes companies make when setting up their email tools, how to best handle certain types of data, tips for providing “done for you” services, and more.

Colin Nederkoorn

How can we make the integration process smooth for different email automation platforms? In this episode, we talk to Colin Nederkoorn, founder of Customer.io. You'll learn about the common mistakes companies make when setting up their email tools, how to best handle certain types of data, tips for providing “done for you” services, and more.

Show Notes 📝

Thanks for listening! If you found the episode useful, please spread the word on Twitter mentioning @userlist, or leave us a review on iTunes.

Key Learnings 💡

Colin Nederkoorn, founder and CEO of Customer.io, describes his company as an "email engagement platform." They cover all communication with their customer's users outside of their apps including email, push notifications, and SMS. To do this well, they collect lots of customer data, but Colin makes the distinction between what they do at Customer.io and other companies that are "customer data platforms" that also happen to include a messaging feature.

Colin's background is in product management. When he started Customer.io with his co-founder, they loved the analytics space. As they heard from more and more customers while making their first version, however, the feedback was clear — their users didn't want another tool to show them what users were doing. They wanted a tool that helped them change people's behavior and helped them better onboard users into their products. Since then, Colin says their team has gone deep on messaging and not as broad with other analytics features, despite having lots of data. 

How do you handle integrations?

Jane and Colin jump right into one of the biggest hurdles faced by email tools like Customer.io and Userlist — data integrations. Colin says:

"Integrations are always hard because they're critical to get right and they require a business to do a bunch of work before they can get any value out of your product. For products like ours, one of the major stumbling blocks for people is being prepared to do the work for an integration."

Colin describes multiple approaches that companies take to address this challenge. One way is to build your messaging platform on top of a popular existing platform. Klaviyo, for example, does this with Shopify providing a "one-click" integration with that infrastructure. This is great when it works, but it isn't always possible.

At Customer.io, their tool is built for those building their own custom platforms, thus making a custom integration necessary. Integrations require engineering time and the process is much different than a one-click integration described in the first approach. Early on, Colin urged customers to integrate with Segment as opposed to integrating directly with them:

"You should integrate with Segment and then turn on Customer.io and Segment rather than integrating directly with us. That way, if we suck, if you have a bad experience with Customer.io, you can just turn us off and turn on someone else. Segment integrates into whoever you want to use."

This approach solved some of the integration hurdles and allowed flexibility for customers, but, nowadays, it doesn't always make sense for Customer.io's smaller users to work with Segment. For Customer.io's larger users, they have a professional services team that helps plan integrations. They don't write custom code themselves, but they are there to help companies get the best experience out of the product.

Handling product data

How customers bring in their data is another facet of the integration challenge:

"Does data come from your data warehouse or does it come from a real-time integration with your product? Companies are exploring whether they should send everything from every app to the data warehouse and then use that as the source of truth for tools like Customer.io."

Colin recommends a hybrid approach between bringing in all real-time data and pulling periodically from a data source:

"The downside with sending everything through a real-time integration is that you're sending a really high volume of really rich data that needs to be processed in real-time. Not everything needs to be processed in real-time."

For larger companies with more sophisticated data sources, this hybrid approach works well to pull in real-time data for when it is truly needed and pulling data on schedule from a data warehouse when it’s not. For smaller companies, setting this type of hybrid system may be unrealistic. In these cases, Colin would recommend a fully real-time integration.

Professional services and integration assistance

Maintaining a professional service team is Customer.io's approach to getting their users to integrate and get value out of the product faster. These services are priced as "neutral" to their customers. Colin says that they aren't looking at their professional services as a profit center and they aren't looking to help with integrations at a loss just to help speed to get customers onboarded:

"Who is going to know our platform better than us, right? It can be much easier and cost-effective for a company to pay us to migrate some complex campaigns from a system they're already using over to Customer.io. We can also help people. We can help give them advice on how to best do the integration and how to best model their data."

While self-service customers still have access to integration advice through the technical support team, professional services are dedicated to premium tier customers.

Professional services are all done in-house and they weren't offered for a long time, in part because the expertise is hard to come by. It also requires the team to be aware of everything happening within the product, without using it themselves daily. Product knowledge at Customer.io is shared through a combination of training materials, regular meetings to educate about product changes, and onboarding but Colin admits that this is a challenge, too.

Jane points out that for many, the perceived difficulty of a services-led integration is the engineering effort and the planning is often overlooked. Colin notices some themes here:

"When we work with more mature companies who have dedicated people responsible for data and analytics, they often have a whole integration plan that they built which shows their data model, all the tools that are connected, and where data is going from place to place."

For the smaller companies they integrate with, it can go smoothly when working closely with an engineering founder but still can be tougher:

"I think where people get hung up a lot is trying to figure out what to attach to the customer profile and then what to send as an event."

Colin sees a trend where companies send all of their data as events as opposed to storing anything on the customer profile. He believes there's room for better education around this distinction and when companies do a good job at finding the correct balance here, integrations run smoothly.

Understanding their customers

Customer.io has found a good fit with customers that are not just B2B SaaS companies, but also B2C companies with mobile applications. They might be small and midsize businesses today but they have aspirations for growth:

"We've built a product that applies mostly to the enterprise in terms of needs. It's a really sophisticated product. It can do lots of things. It has a lot of bells and whistles but at the earliest stages of a company who is trying to be a big company, you can't necessarily afford the tools that are selling into that space. So Customer.io brings the flexibility of an enterprise tool to a different part of the market for these companies who are high growth companies."

Over time, they have learned valuable things about their customers through the sales process. They have found that there is often a mismatch between what companies say they want during the buying process and the features that they actually end up using most. One of the examples Colin cites is the excitement that customers have about A/B testing:

"Very few customers do a significant amount of A/B testing once they sign up. They may not have an audience big enough or have enough data flow, or data points to make an informed decision based on an A/B test. It might take like a year for a B2B SaaS company to get statistical significance on an AB test."

They've also learned about pricing. They currently charge as a B2C and they take care to make sure their pricing doesn't affect their customers' usage habits negatively. Charging based on active users can be difficult to implement well. Ultimately, Colin says:

"We don't want to have pricing that causes our customers to behave in a way that's bad for theirs."

Final advice

Do measure twice and cut once.

“Do a lot of little tests with the tool, and then once you're ready to import all of your data, make sure you've got the data model right. It's going to support all of the automations you want to do.” 

Don't betray the trust in the relationship that you have with your customers and your audience.

"Collect your own first party data, set expectations for what you're doing with it, and treat your customers and their data well."

Thanks for listening! If you found the episode useful, please spread the word on Twitter mentioning @userlist, or leave us a review on iTunes.

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