Using analytics capabilities from Sisu, Fractory was able to identify the repeat business opportunities that fuel growth.
Fractory, founded in 2017 and based in Manchester, England, produces and distributes metal for the manufacturing industry.
The company aims to make the global metal manufacturing industry more efficient by providing a single platform for all parts of the metal production process, and by building a one-stop shop for all metal needs reduce the footprint of manufacturing by lowering transportation needs and lessening the amount of excess scrap metal.
Sisu, meanwhile, is an analytics vendor founded in 2018 and based in San Francisco. Sisu's platform uses augmented intelligence and machine learning capabilities to automatically monitor changes in data sets and then explain why those changes occurred.
In addition, the vendor makes automation a focus, and as it adds new capabilities, a primary focus is automating tasks that can be onerous for humans to perform.
That automation capability proved key for Fractory.
As a startup looking to increase revenue, Fractory needed to identify repeat business opportunities to help develop its sales and marketing strategy. But manually combing through copious amounts of transaction data to the find patterns within that data that point to potential repeat business opportunities would have not only been time-consuming but also nearly impossible.
"At this stage, the most important thing to us is making sure that we're heading in the right direction," Heikki-Albert Tilk, vice president of demand marketing and marketing operations at Fractory, said during a recent webinar hosted by Sisu. "The right direction for us is about the scope of clients and their purchasing patterns."
But the process of discovering those purchasing patterns that lead to growth and ensure Fractory is headed in the right direction is complex.
Fractory offers different metal fabrication processes, payment options, account types, and a host of other options, including a variety of metals to choose from.
Ultimately, there can be hundreds of data points about each customer, each representing a different decision made by that customer.
Heikki-Albert TilkVice president of demand marketing and marketing operations, Fractory
Identifying the combination of decisions -- the purchasing patterns -- that show the highest likelihood of resulting in repeat business was challenging.
So Fractory turned to Sisu's analytics platform for help.
"When you [look] at data in a BI tool, you have to figure out every hypothesis yourself," Tilk said. "You have to slice and dice the data, and there can be millions -- even billions -- of combinations."
Sisu, however, used augmented analytics capabilities to automatically explore all the potential combinations about which customer data points matter most when trying to identify repeat business opportunities, Tilk continued.
"Each combination is, in a sense, a hypothesis," he said. "And for a human being to do it is not realistic."
But rather than taking weeks or potentially months to parse through the data and make discoveries, Sisu did so almost instantaneously.
"It took only a couple of seconds," Tilk said.
Once Sisu identified the combinations of data points that indicate potential repeat business opportunities, the platform used natural language generation to automatically summarize the results of its calculations, explaining the statistical significance of various data points.
Those results subsequently led Fractory to develop and closely monitor three key business metrics -- customer lifetime value, conversion rate optimization and cross-sell revenue -- to look at when making strategic sales and marketing decisions related to any given customer.
Customer lifetime value is simply the total revenue a customer has spent with Fractory, and according to Tilk is the best indicator of whether a customer might continue to spend with Fractory.
But less obvious is conversion rate optimization, which takes into account such factors as industry, company size and job titles when looking to see whether a customer might be interested in more than what they purchased in their initial transaction with Fractory.
Finally, cross-sell revenue tracks the purchase of products and services in addition to those made during the initial transaction between Fractory and a customer and can help identify not only what might interest a customer, but also when a product or service might be of interest to a customer.
One specific customer insight Sisu uncovered was that clients that have credit term agreements with Fractory are most likely to have a high lifetime value.
"Having that fact was essential," Tilk said. "To be able to start proactively going after those leads was a considerable resource."
Meanwhile, the key metrics as a group enable Fractory to hone its entire sales and marketing strategy.
"They help us to focus," Tilk said. "They help us develop lead-scoring to help salespeople know where to focus. They help us create playbooks for salespeople and be proactive. Even if our management or salespeople intuitively knew that something is a good metric, without Sisu they didn't have the data to prove it."