This content, written by Tamara Ford John, was initially posted in Looker Blog on Mar 17, 2020. The content is subject to limited support.
At Looker, we are fortunate to work with some of the most innovative and industry-leading companies. Our customers continue to impress us with the ways they go beyond basic business intelligence to deliver custom data experiences to their internal and external users.
Recently, we got to sit down with Ryan Sherman, VP of Product at , the leading Partner Relationship Management solution. During this webinar, Ryan shared great insights from Allbound’s journey with embedded analytics while building their Channel Insights product.
Here are 5 key takeaways Ryan shared with our team, including why Allbound decided to build a data product and key differences they learned from comparing multiple embedded analytics solutions. If you would like to watch the full recording, you can .
1) Building a case for business insights
When Ryan and his product team meet, their primary goals revolve around building new ways to make their platform increasingly valuable to customers. To do this, they think about opportunities to increase win ratio, decrease customer churn, and create upsell opportunities for existing customers. Before creating their Channel Insights product, they continually came to the same conclusion — additional opportunities to explore data and gain insights would be incredibly valuable to customers.
First, they provided their customers with basic reporting capabilities to provide baseline visibility. The Allbound team noticed that while this increased customer engagement, it could still go farther to help customers discover additional value. When Ryan asked customers how they were using the reports, they seemed happy but he soon learned it was because they didn’t know it was possible to expect more, real-time insights from their data. This is when he knew there was an opportunity to deliver more value at greater scale.
“People were so used to saying ‘this is my limited data. I can export this to an excel spreadsheet, I can create a pivot table’. As I started digging into the process to ask people how they were getting and using data, I was horrified that this was the process that people found acceptable. They weren’t raising their hands flagging that this was a need...When I asked them how frequently they were doing that, they said ‘once a quarter, we try to dig in’. But if you’re going to have success, you can’t look just once a quarter. You have to look on a daily basis to see what worked and create a culture of experimentation. Channel Insights has allowed our customers to create a more outcome-oriented approach.”
2) Why choose an embedded analytics platform
Once the Allbound team was committed to delivering deeper business insights to their customers, they needed to identify the best way to make this a reality.
In doing so, they considered whether building it in-house might be cost-effective and allow them to leverage their internal excellent engineering team. They quickly decided this was not the best path forward, calculating that it would decelerate their internal roadmap by at least six months and still not guarantee the level of insights they were committed to delivering to their customers. They also knew this wouldn’t factor in all the unknowns when developing a new type of product, from development work to the inevitable maintenance requirements. The cost was too great and the return value to customers was not guaranteed.
“We wanted to keep our internal resources focused on our core competencies.”
Once the Allbound team decided not to build the data engine itself, they were able to focus on preparing the data in a way that could be easily productized.
3) Key criteria to consider when evaluating solutions
Once the Allbound team decided to buy an embedded analytics offering, they found their criteria evolved over time as they gained deeper visibility into what platforms provided.
One factor that became increasingly important was customer experience. They found some flashy features, such as extra widgets, actually increased confusion rather than provide value for customers. While conducting user testing, they found a simple and sleek platform was much more intuitive — allowing customers to explore and ask more questions on their own. Since self-service and scalability were key to ensuring the maximum success for Allbound and their customers, they discovered that “more features do not necessarily lead to more value”.
Another key criteria was time-to-value. While every vendor claims to have a fast implementation, the Allbound team also found that in addition to vendor implementation it was also critical to think about the data prep their team needed to do to prepare for any solution. In the interest of fast and scalable deployment, the Allbound team chose to use the hosted option from Looker vs. managing the DevOps on their own. This helps them efficiently serve their customers and keep their internal team focused on their core competency.
“With Looker, we were able to do a very rapid implementation which consisted of a week-long POC, followed by a kick-off call. In the middle of the kick-off call, the POC was so easy for us to implement that we did an alpha release to a few of our key customers in the middle of the kick-off call.”
Another key factor to think about is documentation and support. From a developer standpoint, their team appreciates the documentation, in-app support, and suggestions while developing in LookML.
In providing their customers with more ways to answer questions than ever before, the Allbound team found it critical to maintain security, scalability, flexibility — ensuring customers could continue to ask more and more questions while guaranteeing secure performance. By using an analytics platform vs. an in-house-built DIY product, they have been able to maintain flexibility as their needs have changed.
“With a platform like Looker, which is data source agnostic, you can switch your data source and still use the same queries without needing to rewrite everything. It also keeps all of your developers writing all your queries in the same exact format. It creates a method to make sure you get accurate and consistent results.”
Finally, the Allbound team found the total cost of ownership to be very difficult to predict across some embedded analytics tools. They found that some platforms charge for user licenses and server licenses, in addition to the internal developer and DevOps costs. In the end, they decided to have Looker manage their DevOps to protect against performance issues and additional server costs as they scale.
“If you’re just paying per-user license model and fixed server model, then you’re not taking into account economies at scale. With Looker, you’re paying a per-user license but that fee goes down significantly as you start increasing your user license rate...that generates significant ROI and your cost goes down.”
Ryan’s biggest piece of advice when evaluating different embedded solutions?
→ Do side-by-side comparison POCs with your top choices. Getting your own experience with the tools and team is the best thing you can do to find the key differences and right solution for you.
4) Generating ROI through data
It’s critical to talk to your customers to understand what their KPIs and goals are so you can help them uncover additional key metrics and insights that could provide value. By focusing on providing the most value to their customers, the increased internal value has followed for the Allboud team.
Since launching the new Channel Insights, Allbound has experienced a 30% increase in revenue from new contracts and upsells from additional customers. The value hasn’t stopped there. Using Looker has also helped save their team time by providing intuitive self-service reporting to customers and therefore increased internal efficiency. It’s also decreased customer churn rates and helped their customer success team easily spot areas for improvement and demonstrate platform ROI.
The Allbound team is continuing to identify new ways to provide greater value to customers by asking how they’re using the Channel Insights product — making sure they’re using the platform to its full potential and generating ideas for new product advancements. The Allbound team is also working to augment the data they have by pulling in more and more data with other business APIs (ex. Clearbit) to more easily help their customers identify and take the next best steps. Allbound is determined to not just show data but to deliver clean actionable insights.
5) How Allbound created a competitive advantage
Since using their new Channel Insights product, customers of Allbound have been able to decrease their average partner activation time as well as discover and drive activities that lead to the most successful channel interactions. Soon they will be able to understand their ideal partner profiles with augmented data from their most successful partners. All of this has resulted in Allbound customers being able to scale their partner management programs by exposing where partner managers can best focus their time and energy.
While initially worried that industry analysts and customers would see embedding Looker as a shortcut, the Allbound team has found the opposite to be true. During calls with research firms such as Forrester and customer feedback calls, the feedback has been that they appreciate this level of technical investment from Allbound. By Allbound providing their expertise of the space combined with the power of Looker, Allbound is able to deliver their customers unparalleled value.
We couldn’t possibly capture all the great tips and expertise Ryan shared on the webinar, so be sure to . Thank you to Ryan and the Allbound team for sharing their story; we can’t wait to see what they do next!