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AiThority Interview Series With Ray Zhou, Co-Founder at Affinity

Ray Zhou

Marketers and sales professionals should really understand the capabilities and limits of AI and automation. They should know what AI is good at!!!

Know My Company

Tell us about your journey into technology and how you started Affinity.

My co-founder Shubham and I were roommates at Stanford, and we had talked about starting a business together. At the time, we didn’t really know what type of business we wanted to start, so we made a point of talking to as many people as we could from a variety of fields and in a variety of roles — everything from entrepreneurs and investors to small business owners and executives. We ended up realizing that no matter what job a person held or what role they filled, their success all hinged on one thing: building relationships with other people.

Of course, we also realized that there weren’t any good technology tools out there to let people build and nurture those relationships. So we set out to create something that would let them do just that, and that became Affinity.

How do you bring data intelligence into a CRM?

Affinity’s core thesis is that people’s relationship data is best captured in our everyday communications, specifically email and calendar. These channels capture who we know, where we know people from, why we know them, etc..

Incidentally, every relationship-driven company — from investment firms to sales and marketing teams to real estate firms — is sitting on a ‘goldmine of data’ in the form of their raw communications, which is generated at an incredible rate. Yet, no one is leveraging this data to its full potential.

Email is a really incredible form of communication. It’s ubiquitous and used for pretty much all external business communication. Calendars are similarly ubiquitous. This means that virtually every professional relationship that matters is captured somewhere in a stream of emails and calendar events.

The email graph is one of the most interesting datasets on the planet — it contains a ton of interesting information about who knows whom, how well they know them when they were last in touch, who’s making intros to whom, and so on. The problem is that there is way too much of it, and it’s not structured in a way that’s easily accessible, sharable or visualizable.

So, this is what Affinity does.

Once users link their email and calendar accounts to our platform, we sit on top of that communications data, extracts insights from it, and build not one, but a whole stack of next-gen interfaces and tools and visualizations on it that helps our users manage their workflows and their networks more effectively.

We’ve brought this into CRM in three ways —

– First, we use this information asset to massively reduce the amount of data entry that a team normally would have to do in order to manage relationships. Everything from logging calls and creating contacts to entering notes from call transcriptions and capturing status updates on deals.

– Second, we’ve built intelligence tools that help our users prioritize their relationships. It’s easy for any rep to get overwhelmed  by which deals should they be focusing on. With the amount of information available today, CRM systems should be able to go from being systems of record to actual prescriptive platforms where they’re helping the sales rep throughout their days on which deals to reach out to, where the ball is being dropped, etc.

– Lastly, we’ve used this data asset to build a CRM that actually helps you better leverage your network and break into new accounts by revealing the most promising opportunities inside it. There is still a ton of work to be done by most (if not all) CRM players on how they analyze data to produce relational insights on which accounts reps can get warm introductions to — this will likely be a game changer in the long-term.

Tell us how AI, account intelligence and CRM fit into a modern CMO’s tech stack?

Modern marketing and sales teams must be aligned and the only way to properly do that is to be laser-focused on who you are going after and why.

With the recent advancements in AI, technology can help guide us to the best opportunities. As for CRMs, this is now a shared platform for sales and marketing as both need to be strategically thinking about revenue. AI enables CRMs to actually work for you. At Affinity, we leverage machine learning and natural language processing to auto-populate your CRM workflow and augment data with relevant facts in real time.

As a mentor in tech industry, how should young marketers and sales professionals train themselves to work better with AI and Automation?

Marketers and sales professionals should really understand the capabilities and limits of AI and automation. The should know what AI is good at: automating highly structured, repetitive tasks like entering data; generally classifying things (with an always-existent margin of error), predicting structured events (with fallible confidence scores), etc. They also need to know what automation and AI can’t do (yet): making complex judgments like whether a deal is good or not, writing and sending emails for you to account for all of the different situations you could respond to, etc. These are tasks that are simply too complex and unpredictable as of yet for AI to replace.

They certainly won’t be replacing what you do today, and if you are selling them, most likely you will disappoint your customers. There are a lot of companies touting that they do AI today and overpromising on its capabilities.

Where do you see pipeline automation tools in 2020?

I think we’ll see automation of the most tedious tasks around information entry, as mentioned above. Logging calls, creating contacts, taking notes, updating statuses, recording interactions.

AI will automatically understand everything about a relationship in a pipeline and fill in hundreds of parameters autonomously — from how a prospect was introduced to sentiment analysis to industry and job title matching and much more.
Since computing power is cheap, we’ll find ourselves swimming in a ton of automatically entered fields. We don’t have to use all of them, and that’s not a problem. Having them available will allow humans to run sophisticated higher level analyses on their pipelines that weren’t possible before.

I think we’ll also see AI take an extremely active role in building the pipeline itself. We’ll have sophisticated matching algorithms that can seek out accounts similar to your targets, or accounts that have a high probability of closing. These algorithms will be automatically computed against a ton of factors, from qualitative similarities like industries and job titles and communications or social media behavioral habits… to the probability of getting an introduction or connection.

Lastly, I think we’ll see a lot of reactive pipeline tools emerge. For the first time, opportunity pipelines will seem to have minds of their own — they’ll understand when opportunities are being dropped, flag when specific actions can be taken to drastically improve close rates and more. They’ll know what patterns of behavior (e.g., rep communication habits) lead to the most closed deals and passively recommend those actions to other users.

How closely do you follow predictive intelligence technologies?

I don’t follow any predictive intelligence publications specifically, but read a lot about it in the context of other research happening. I always have a pulse on the latest in the industry, especially on the relationship intelligence side.

Would most businesses turn to AI eventually for better performance?

I think we will likely see the automation of more tedious jobs or machines doing the more manual things to enable humans to do what they do better. In our opinion, machines are really good at analyzing data, parsing out empirical insights, and serving them to humans to take action on them at scale. There are many other tasks that require creativity or strategic thinking on behalf of humans, and these will be impossible to displace.

Elaborate on your playbook for better client-facing interactions. How do you pass the benefits of your real-time analytics to customers and tech partners?

Technology will never replace human interaction. With technology doing the heavy lifting of relationship building (managing who our team has talked to, when and the nature of the interaction), we can spend more time having genuine human interactions with our prospects, clients and investors.

How potent is the Human-Machine intelligence for businesses and society? Who owns machine learning results?

I think in the modern business everyone owns the results. Tools like Affinity leverage machine learning to analyze data and constantly be producing analysis that can immediately be leveraged.

The Good, Bad and Ugly about AI that you have heard or predict –

The Good is that we will see massive productivity gains with the advent of AI, especially across all relationship driven industries. People will spend a lot less time doing tedious tasks and a lot more time focusing on nurturing and growing relationships. Their everyday intuitions will be augmented by AI in many ways — from suggestions on what opportunities to go after to communication habit changes that improve the quality of interactions.

The Bad is that there is a lot of overpromising around what AI is capable of today that simply isn’t true yet. There are things that companies claim they are capable of doing that is not feasible. Ultimately, AI should be seen as a means to an end, not the end itself. It’s just another tool to develop incredible products and systems. The north star of a startup should be developing the best possible solution to a problem given the most cutting-edge limits of technology, not claiming to pioneer AI in new sectors for the sake of claiming to be an AI startup.

The Ugly is that long-term, I think people seriously underestimate the dangers of AI. This is more philosophical, but human intelligence is the most upstream source of all of our ideas and inventions. We’re close-minded about this — it’s hard to imagine what a digital intelligence drastically smarter than us could even look like. This makes its advent a lot more sudden and unpredictable and will likely take us by surprise. I’m not sure when that will happen necessarily, but it’s something to be cautious of.

Nick Bostrom has a great book called Superintelligence on this. While on a day-to-day basis, there aren’t drastic fluctuations on the front of what AI is capable of, zoomed out on the macro level it has actually beaten a lot of predictions and has been advancing at an incredible rate. On the time scale of 50 to 100 years, it’s very hard to predict what will happen.

The Crystal Gaze

What AI start-ups and labs are you keenly following?

The most interesting work is done by research institutions like OpenAI, DeepMind, Vicarious, etc. I try to keep a pulse on everything that happens in the SaaS industry, specifically around CRM, as well — mostly through their marketing and newsletters and other things like that.
I also have a passive interest in the autonomous mobility space and some of my smartest friends and even my brother work in companies on this cutting-edge — companies like Tesla, Zoox, Cruise,, etc.

What technologies within AI and computing are you interested in?

I’m really interested in Natural Language Processing. NLP is an exciting branch of AI that combines the powers of AI, computational linguistics, and computer science. It enables computers to process, understand, and generate human speech and text. By bridging the gap between people and machines, NLP is changing the ways that businesses understand and analyze data.

What’s your smartest work related shortcut or productivity hack?

My biggest productivity hack is simple: stop multitasking.

Try to focus on one thing at a time. I find that when I try to do too much all at once, not only does it take me longer to get it done but the quality of the work suffers as well.

Tag the one person in the industry whose answers to these questions you would love to read:

Brexton Pham, who’s working on a stealth AI company, and Alin Bui from Anduin Transactions

Thank you, Ray! That was fun and hope to see you back at AiThority soon.

Ray Zhou, Co-founder, Affinity


Affinity is a relationship intelligence platform built to expand and evolve the traditional CRM. Affinity instantly surfaces all of your team’s data and shows you who is best suited to make the crucial introductions you need to close your next big deal. Using AI and natural language processing, Affinity helps your team curate and grow its network by unlocking introductions to decision makers and auto populating your pipeline to increase deal flow.

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