Today I’m talking to Shubham Goel, who is co-founder of Affinity, which provides relationship intelligence solutions that use machine learning algorithms and natural language processing to analyze data and help companies make better decisions about customer relationship management.
Shubham, before we talked about Affinity, and how you differentiate from other CRM solutions, can you tell me a little bit about yourself, and the company.
Yes, and please call me Shooby. I am one of the founders at Affinity and responsible for our marketing, finance and operations. I’m an engineer by training, so this role is relatively new for me. I grew up in Delhi, India, and prior to Affinity, I was at Stanford, studying computer science and artificial intelligence.
About the business—we started it almost five and a half years ago. We noticed when we started the company there were lots of industries and companies out there whose businesses are extremely relationship driven as opposed to transactional: businesses with long sales processes and many relationships that they have to manage over multiple years.
Examples include financial services, commercial real estate, professional services, and consulting. And we realized that the legacy CRM solutions that they were using just weren’t cutting it for them, for a couple of reasons
First, people had to enter a lot of data into these CRMs—and guess what? Nobody wants to do data entry. They had the software, but so much missing data that the software was not that useful. This led to the second problem—with incomplete data, the insights were also missing. These businesses wanted to answer questions like, “Who in my organization knows anybody at a company I want to reach out to?” or “Who can introduce you to the right people to build relationships in a certain location?” But they didn’t have the data to answer these questions.
What’s Affinity’s approach to solve for that?
We realized that much of the really powerful real-time data about our relationships does not live inside CRM systems—it lives inside our communication streams. You and I are on the Zoom call together, we exchange emails and calendar invites, and these interactions paint the richest, truest picture of who we know and our relationships.
Affinity has built a platform to capture this data, from email, calendars, phone calls, data from the public web, and social media—and bring it all together in one place. On top of that we’ve built a natural language processing layer that understands what the data is telling us about the team’s relationships. This all comes together in our next generation CRM product. It’s powerful because it lets our customers take advantage of this enormous data asset
What’s the onboarding process like?
Onboarding is very simple to get customers up and running quickly. You sign up for a demo and a trial, to see the value of the solution. Once they decide they want to buy, it takes a few days to import data from other systems, such as a legacy CRM and communication systems. It’s certainly not a five-month onboarding process with consultants. It’s very much out of the box ready, really easy to use, and very automated. We go from signing up a customer to them fully having it deployed within a week.
Other CRMs pull in information, like from email and other communications systems too, but as I understand, this is just step one for Affinity, correct?
Yes, we collect this data from these different systems and then we synthesize and analyze it using a natural language processing layer on top of the data, which tries to answer many questions and surface what you need to know about the relationship.
Think about the information hidden inside each email. Is this email an introduction, or somebody who we have a strong relationship with? Is the person’s phone number or job title in the email? Is it an email that needs a response?
As this data comes in, it starts answering questions and then surfaces information to the user, such as this contact has a new job, or has moved to a new location. Or here’s the best point of contact that your organization has to a person based on the number of interactions they’ve had.
What types of companies are you targeting?
We have a very vertical market strategy, targeting relationship-driven businesses. We started with financial services—investors, venture capitalists, private equity firms, and investment banks. Also, companies like Qualcomm, that have venture, innovation, and business development teams, all of which are relationship-driven.
Another key vertical is commercial real estate, both brokerages and landlords. We’re starting to work more with professional services firms also.
Businesses where you have to keep your network warm, and you don’t know where your next deal is going to come from—an asymmetrical sales process where you might build a relationship over three years and then suddenly a deal happens.
All told, we have about 1,500 customers in 70 countries.
Do you have an example that you can give about how a current customer is using Affinity?
Let’s take an example of a venture capital firm that’s responsible for raising money and then deploying that money to startups. They can use Affinity to manage their deal flow process and pipeline on Affinity, helping them to determine where to invest.
Fundraising is another workflow example. When a company is trying to raise money from high net-worth individuals or pension funds, they can manage that process and those relationships on Affinity.
And they’re using Affinity to answer the types of relationship-driven questions. I mentioned earlier. And they’re doing all of this much more quickly. Customers tell us they had no idea that they had connections to so many people—it was all buried in our email and inboxes, and suddenly it comes to light. Now they can access that institutional knowledge from one place.
How is Affinity priced?
We have three tiers of pricing. It’s a per user per year subscription. The tier that most folks buy is the middle tier, which is $1,800 per user per year. That includes all of the things we’ve talked about, managing pipelines and relationships and getting contacts across the team. It also includes reporting, and real-time KPIs, sort of a proactive analytics suite.
Looking ahead, what are your plans?
Affinity is in a really interesting place. We will also improve the product—we’re only just scratching the surface of what’s possible with this natural language processing layer, and there is a lot more we want to do there. We will continue to invest in data and in our ability to understand and process data into useful information. And we must stay focused on making the value of this technology very clear and obvious to our users.
We are becoming a brand name in the financial services world, and will continue to focus on this sector. We’ll also drive into other segments that I had mentioned: commercial real estate and professional services where we’re not yet as well known.
The challenge is that we have about 110 people and are growing very quickly. We face a steep change in how we manage the business and scale the culture of the business. We need to be thoughtful about how we hire and on-board people over the next year and do that well. It is hard technology to build—that’s why not everyone is doing it. We need the best talent to get to the next level.
Well, Shooby, thank you so much, I really appreciate your time. Readers can visit https://www.affinity.co/ for more information.
© SMB Group, 2021
Source: Laurie McCabe’s Blog