The Startup: Ender Turing
Ender Turing’s story starts with research on the topics they later used to build their product. Co-founders were researching everything around machine learning, AI, and speech recognition.
They created technology that was able to “understand” the contents of the call and began looking for how it can be applied to businesses.
They had the technology and built a product up to some level, however, they realized they did not know a lot of the things that startups needed to succeed. That’s when they decided to join MIT EF CEE.
Today, their call center performance management software is used to speed up quality control, train entire teams, and boost customer satisfaction.
The Partner: CreamFinance
CreamFinance Poland is part of an international LendTech group AvaFin operating in six markets: Latvia, Czechia, Spain, Mexico, Poland, and Austria (headquarters).
It owns several different brands, including Lendon.pl, its most well-known online loans brand, and ExtraPortfel.pl, which operates in the Polish market.
Even though the company was founded over 10 years ago and is today operating successfully in several different markets, it’s still trying to act and operate in a startup-like way.
That internal need to stay on top of the latest innovations resulted in the company’s search for startups that could help support its core operations.
Partner’s Key Problem
CreamFinance’s call center agents perform thousands of calls every day. Those calls fall into one of three key categories that are critical to the company’s success:
- Customer service and sales.
- Phone verification, right before the loan gets approved.
- Debt collection.
Each of those areas requires different skills and training strategies.
The problem is, the huge number of calls makes it impossible to verify, categorize, and process all of them manually.
Of course, the company leverages sample calls to train their team and create scenarios. But those samples cover a small percentage of all calls.
In fact, it’s estimated that only around 5% of all the calls are checked manually. This means 95% of all calls never add any extra value to the company. On top of that, when they’re checked, most of the time, the calls are picked completely randomly, which leads to difficulty in creating the best training material
That randomness then influences areas of training for people in the contact center. As a result, the training process is far from being as efficient as it could be.
And while there were solutions capable of processing the calls, they were usually complicated, expensive, and didn’t address key challenges that CreamFinance had.
Not to mention that none of them worked correctly with the Polish language – which is one of the hardest languages on Earth.
But, that’s where Ender Turing came in.
Ender Turing’s Solution
Ender Turing created a solution that allowed CreamFinance to leverage AI and speech recognition to analyze all its calls and understand their content.
It gave them a tool that they can use to categorize the calls, quickly create key statistics, and answer critical questions, such as:
- What are the recurring themes of the calls?
- What questions do the callers ask most frequently?
- What are some of the most popular keywords?
The tool allows them to train their agents using a lot more relevant materials. It also helps improve call scenarios, increasing customer satisfaction and improving the outcomes of the calls.
But, the two would never meet if Ender Turing didn’t join the MIT EF CEE Accelerator Program. Interestingly, CreamFinance wasn’t even the first partner that Ender Turing got assigned at MIT EF CEE.
MIT EF CEE Accelerator
When Ender Turing joined MIT EF CEE, they had the technology – but they lacked business guidance. They didn’t know how to get funding, how to market, or how to scale their solution.
The fact that their solution was aimed at enterprise clients only complicated things. After all, such big clients are not easy to work with – not to mention how hard it can be to land one.
That access to enterprise partners was one of the reasons why they chose MIT EF CEE. Most other programs they considered were focused on small SaaS solutions.
MIT EF CEE’s strong network of enterprise partners was exactly what they needed to grow.
And while they initially got assigned to a different company, they quickly realized their goals were not aligned.
But, thanks to their unique product and MIT EF CEE’s trusted brand, they managed to secure a partner – CreamFinance – in the open market.
- Cooperation Challenges
During their accelerator’s partnership with CreamFinance, Ender Turing created a successful PoC. But, the biggest challenge came with understanding the specific needs of their partner. They had the technology but lacked a full understanding of business processes.
CreamFinance helped Ender Turing understand the processes and regulations surrounding their business. They also provided them with in-depth feedback regarding their technology.
The key to success for Ender Turing was to stay open to their partner’s business needs. They reacted to all feedback very seriously and were very open to implementing new functionalities.
Thanks to excellent communication, it sometimes took them just a few hours to change and test a new feature, which significantly accelerated their PoC development.
Another challenge, this time on the partner-end, was caused by the differences between the systems used by Ender Turing and those used by CreamFinance.
The key to success for the partner was to try to become more flexible and responsive to the needs of the startup that they worked with. Of course, as an established business, they couldn’t go around certain processes.
But, even though the system changes required additional work, they’ll ensure better compatibility with the startup’s solution in the long run.
The final product exceeded CreamFinance’s expectations. The company went from monitoring a small percentage of select calls to analyzing 100%.
They can understand the content and the context and get significant data that are key to training call center teams and improving their performance.
On top of a tool for monitoring calls they had hoped for, they received one to increase call quality, give feedback, and educate their teams.
For Ender Turing, the cooperation ended in signing a commercialization deal, which was their #1 success measure.
On top of working in the Polish market, they already signed a deal with CreamFinance Spain and are close to signing one with CreamFinance Mexico.
The two destinations are a chance for Ender Turing to understand Spanish-speaking markets and their unique needs and challenges. It’s also an opportunity to prepare Ender Turing’s solution to operate in Spanish, which opens them to markets with a total population of over 450 million.
Thanks to all the feedback, guidance, and resources that they received during the Accelerator Program, they were able to build a commercial product that they’re now offering to a range of different companies.
Lessons Learned from a Partnership with an Enterprise Client
One of the key lessons for Ender Turing came from working with an enterprise client. That’s when the success of the partnership is no longer just about the product but everything that’s related to how an enterprise client operates.
This includes compliance, security, and regulations. All that’s often followed by a lot of paperwork and internal (and, often complicated and time-consuming) processes.
That experience, and everything they learned during the program, prepared them for working with other enterprise clients which, they believe, would not be possible if they didn’t join the accelerator.
Key Takeaways from Working with a Startup
For CreamFinance, the most important takeaway is to not be afraid to work with a small company. They believe that often, an innovative, flexible, and driven startup team can have a much better solution to a challenge faced by an established business.
That initial “fear” is also an important lesson for startups – which they believe should not be discouraged if initial feedback is not as they expected. What’s even more important is that they believe in their product and find a partner whose business needs are aligned with that product.
Of course, that initial alignment is just the first step. Every successful cooperation requires mutual trust and openness. To succeed, it’s critical that both parties work on understanding each other’s needs and challenges. After all, the project is successful only when both parties reach their goals. That lack of mutual understanding is often the reason why similar partnerships fail.
Thankfully, in this case, both parties worked hard to support each other. And, thanks to Ender Turing’s openness to feedback, responsiveness, and commitment, they were able to create a successful, fully-functioning product that met CreamFinance’s needs and was ready for commercialization.