The insufficiency of accurate SMB data is an obvious void in the financial and e-commerce sectors. As the age of digitalization evolves, companies see sales and retention opportunities rise left and right, but with very little to no tools to fully seize their potential. From extensive research to relentless solution scouring, the need to revamp the traditional approach to enterprise data has never been more urgent.
We had the chance to interview Leetal Gruper, CEO and Co-Founder of Tarci, a company that uses a continuous intelligence engine that regularly collects, analyzes, and translates billions of signals from diversified sources, turning big data into actionable insights. Their dynamic data already drives the increased efficiency and productivity of customer-facing teams at Fortune 200 companies, including leading financial institutions, insurance companies, and enterprises that sell to small and mid-size businesses.
Tarci’s aim is to improve ROI at every touchpoint in the financial and e-commerce sectors through insights and dynamic data. What were the market gaps that you’ve noticed that led you to the foundation of Tarci?
Before co-founding Tarci, I headed the sales and retention teams at Worldpay (the largest payment company in the world). One of the key challenges we faced was the lack of accurate data about SMBs to make the unit economics work. We spent far too much of our time researching and qualifying small and mid-sized business prospects, and far too much of our budget on buying expensive SMB lead data that was often outdated or just plain incorrect.
There was a clear void in the market that needed to be filled. It was time someone found a way to generate true, up-to-date SMB data that could be used to identify real opportunities and build long-term, mutually beneficial relationships with small and mid-sized businesses. So, along with my co-founder Sergey Bahchissaraitsev, that’s what we did.
What were the challenges you encountered before finally cracking the code for capturing SMB data for businesses?
From the start, our goal has been to provide a full actionable picture of small and mid-sized businesses that will save marketing and sales teams time and money while increasing revenue. We realized very early on that we would have to shed the traditional approach to enterprise data used by data companies. Small and mid-sized businesses operate differently than enterprises, and they change at a much quicker rate. Not only that, but their data is scattered everywhere, and it’s not consistent from one business to another, or even from one industry to another.
However, after considerable time and effort, we developed a new approach that allowed us to gather multiple data pieces from multiple sources and stitch them all together, giving us a full picture of each business. It took a lot of thinking outside of the box, but we found a way!
Walk me through your proprietary continuous intelligence engine in connecting a wide range of data sources. How does this technology work?
When it comes to getting a true view of SMBs, you need to analyze multiple data points from multiple sources all the time.
For example, if a restaurant is planning to open a new location, it typically won’t issue a formal announcement before it is opened. However, they do leave clues in the ordinary course of doing business, such as an application for a regulatory license, job board listings, or a “coming soon” announcement on their website. Along with the SMB’s firmographic and technographic data, Tarci’s continuous intelligence engine uses advanced data science techniques to compile and decipher these clues.
Because our engine is always learning and building on the data, it can detect changes that indicate potential new opportunities. The result is dynamic data, which gives you a unified, actionable view of SMBs and their needs.
What are its key differences from utilizing static data?
Let’s say you have a list of prospects derived from static data from a traditional data provider. From that list, identifying prospects that are relevant, active, and in need of your offering is like fishing in the dark. You can cast your line, but what you catch comes down to luck.
With Tarci’s dynamic data, there’s no luck involved. Our data lets you see businesses clearly and identify those that not only meet your ideal customer profile but are also at a point in their life cycle where they likely have a real need for your solution. With dynamic data, you get real-time indications of opportunities. Focusing on those ripe opportunities can lead to more closed wons and shorter sales cycles, reducing your cost of acquisition. On average, our clients are seeing a 15% reduction in COA.
The other thing static data can’t tell you, but fresh dynamic data can, is if a business is growing or declining. According to the U.S. Small Business Administration (SBA), roughly 70% of all new businesses survive for the first two years. At five years, the chances of success fall to about 50%. If you’re blindly targeting SMBs using static data, the odds of building long-term, profitable relationships aren’t great. But by incorporating dynamic data into your toolkit, you can focus your efforts on SMBs that are on a growth path and far more likely to give you higher lifetime value.
With more closed-wons, lowered COA, and higher LTV, Tarci’s dynamic data outshines static data every time.
One of the most fascinating features of Tarci’s solutions is its capability to anticipate customer needs, which is key in unlocking revenue in the SMB payments market. What are the outputs that customers can expect in finding SMB opportunities in terms of a) researching prospects, b) qualifying first call, and c) closing deals?
Our clients don’t have to research or find SMBs that meet their ideal customer profiles - our data finds those SMBs for them. When we first onboard clients, we work with them to understand their ideal customer profiles, and to discuss what life cycle changes in those ICPs may result in needs for different offerings. We then suggest which tags and events to use as filters so that any SMB data delivered to our clients will be highly relevant to their goals.
Using Tarci data to drive the who, when, and why of their outreach, our clients have reported significant improvements to their email and telephone response rates - in fact, on average, they see 6x the engagement.
And not only is data indicating new needs such as financial services or software incredibly valuable from a prospecting perspective but from retention and upselling perspective as well. Imagine being able to keep an automated eye on your existing customer base, and reaching out right when a need is surfacing for a new or upgraded service. Our clients have reported a 25-35% decline in customer churn with the incorporation of Tarci data into their cross-selling/upselling efforts and a greater focus on growing businesses.
Another key feature is Tarci’s predictive insights capabilities to protect businesses from bad commercial debts. Can you talk about how Tarci’s technology enables businesses to spot early signals of vulnerable customers?
We don’t just track business growth - we also provide insights about potential financial vulnerability. If an SMB is downsizing, for example, that could indicate a need for closer review before issuing any type of loan or credit. And again, our data is industry-specific, so even something like a change in license status or a reduction in service offerings could serve as a flag for our clients to review more closely.
Having a real-time view of the business protects both our clients and the SMBs they serve from the negative impact of commercial bad debt.
Just like every other cutting-edge technology, CRM integration is crucial. Can you talk about the integration process of Tarci to platforms like Salesforce and Hubspot? What do companies need to provide?
Yes, it was very important to us that our clients could easily incorporate dynamic data into their existing workflows. We have made integration with HubSpot and Salesforce very easy - in fact, one client recently commented that it was one of the simplest and most understandable integrations he has ever performed, and he’s performed many.
All a company needs to provide is some critical thinking. The key to successful integration is to consider exactly how you want to use the data and then map the fields properly. We provide a complete integration guide, and will also walk you through the process. The technical piece is easy - the critical part is making sure that the data is integrated in a way that feels intuitive and useful to your teams, and even that’s not hard once you consider your existing processes!
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