SalesTechStar Interview with Paul Kleen, Founder and CEO at Pitchit

Paul Kleen, Founder and CEO at Pitchit talks about the benefits of AI powered lead qualification processes and how it can drive more optimized sales and marketing cycles in this catch up:

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Hi Paul, tell us about yourself and what inspired Pitchit?

I previously led two Y Combinator startups through acquisition: as Head of Growth at Paperspace (Y-Combinator W15; acquired by Digital Ocean) and as a data scientist at Framed Data (Y-Combinator W14; acquired by Square). I began my career as a key account sales executive at Gannett (one of the largest agencies in the USA) where I conducted full cycle sales activities and managed sales for key clients including Lucky and Hy-Vee grocery chains. There I had to fill a pipeline and qualify leads, at scale, in order to hit a sales quota. Later on, I worked at Framed Data as a data scientist. There I analyzed the data of SaaS businesses to help discover which customers were likely to churn or upsell, then used the Framed Data application to guide users on how they could take action to prevent churn or encourage upsell actions. Pitchit combines these two experiences because the application uses machine learning and AI to help aid sales teams who are qualifying leads at scale. Creating Pitchit required a strong understanding of the manual labor challenges a sales development rep (SDR/BDR) faces when qualifying a new inbound lead, as well as how new advances in AI and machine learning could aid sales teams by accelerating some of these activities that were traditionally done manually at a heavy cost to the employers.

I had personally spent $100M+ in online advertising at my various past roles, and seen how hard it was to manually qualify leads from advertising campaigns. Very often the marketing team and sales team don’t get along, and show different reports to the higher ups. With pixels being relegated, and the fragmentation of the digital media landscape, the gap between a marketing-qualified lead (MQL) and a sales-qualified lead (SQL) was growing every year, and both marketing and sales teams were being negatively impacted by this trend.

I wanted to make the sales development role more profitable for organizations selling at a high velocity. Think of a team that gets hundreds or even thousands of leads every month. At that scale, lead qualification takes multiple full-time roles and humans often fail to be able to do the work profitably. Sales development reps should be able to spend more time talking on the phone or in Zoom calls, and less time doing the legwork to qualify a lead to get them ready for the phone call.

I envisioned one unified inbox, powered by AI/ML, that could aid sales teams in accelerating the initial steps of qualifying a lead, regardless of the channel that the lead came from. For instance, I imagined a consumer direct messaging (DM’ing) a brand on Instagram, then magically being in a live chat conversation with an AI agent asking them a qualifying question, then all of a sudden their phone rings with a live representative on the line, helping the now qualified consumer make a purchase over the phone. I also envisioned a consumer going through a traditional website funnel and filling out a form, then immediately having a 1-to-1 conversation via text message with an AI agent asking them some qualifying questions, before transferring them to a live agent. These two scenarios were very hard (if not impossible) for brands to support, at scale, 24/7 when using human resources. But this is what consumers want from brands; to be able to purchase from them when they want, where they want, and on whichever channel they want.

We’d love to hear about your recent funding and the challenges you might have faced while procuring the round?

It all starts with how I met Plug and Play Tech Center. I had a proof-of-concept product and one of my first customers, Sam Bigdeli, just so happened to be well connected to an investment associate at Plug and Play, Mohammad Reza. Plug and Play decided to invest in Pitchit, and put us on stage at their Fall Summit in 2023. Silicon Road Ventures was watching that presentation virtually and contacted me, which ultimately led to them leading a Series Seed round and becoming the largest major shareholder. Gray Ventures is another Atlanta based fund that knew Silicon Road Ventures through local networking, and I pitched them next. The story ultimately boils down to just working a network of connected investors. One person led to another person, and I followed the trail to round up a nice group of interested investors all within a few months.

We oversubscribed our round. Silicon Road Ventures told us they spoke to 236 startups before deciding to invest in our company. Gray Ventures said they are becoming active investors again after sitting out for most of the 2021 hype, because they saw companies were too overvalued. Thomson Nguyen said the environment was very hard for most of the companies in his portfolio and that we had a strong pitch that cut through the noise in a tough market.

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What are some of the core mistakes sales and marketing teams still make when it comes to lead qualification?

Throughout my sales career I saw the same series of events happening in this exact sequence:

Leads were very expensive to acquire through advertising and marketing.

Sales teams were too slow to get ahold of them (in my research, sales teams kept 63% of their leads waiting 15 minutes or more before finally contacting them).

When sales teams can’t provide an instant customer experience where they contact inbound leads immediately upon those leads showing interest, their close rate drops dramatically.

When close rates are low, the cost per sale becomes astronomical so the business decides to shut down the whole marketing funnel, and people lose their jobs.

Insight Partners did a study on their portfolio and found that SDRs only contributed 18% of the sales pipeline value, yet they are funded as if they were producing 40% of the sales pipeline value. This 22% gap results in a net loss that isn’t sustainable. AI can close that gap, and even make it profitable, therefore provide a net profit and justify increasing headcount in the best case scenarios.

Given the new technological leap that AI has brought to the marketplace, we are finally able to provide a solution to this doom loop. In our customer case studies, we’ve seen a 250% increase in qualified leads when sales teams add Pitchit to their lead qualification process. This has made cost per sale lower, and therefore has saved sales jobs that ultimately would have been lost had they not utilized Pitchit.

How are you seeing AI enhance not just lead qualification protocols but also lead generation tactics; a few AI enhancements from the market that have piqued your interest here off late?

After we launched our API, we had 6,000+ new web applications that could integrate with Pitchit at various stages of the lead qualification process. We have seen salespeople do some really cool things, and there are a few that have stood out to me so far. One of our customers integrates all of their Facebook / Instagram comments into Pitchit because they couldn’t historically get any sales from those conversations due to how infrequently they checked their comments feed. Our AI agents have been able to instantly engage those comments and take the conversation into direct message threads that actually lead to booked calls / sales. Another customer was having trouble getting ahold of leads over the phone via Five9, even after that lead had opted in and asked for the call, so they integrated Pitchit after a failed call attempt. This allowed our AI agents to do all of the follow up work to get that lead talking again, at which point the sales team regained engagement without all of the usual legwork they had to do historically. Another good example is a client who integrates their form fill directly into Pitchit. Our AI sales agents immediately start to qualify those leads, score and rank them, and then sync only the hottest leads into their CRM, at which point their sales team has to manually take over the lead. All of the above are really innovative ways that Pitchit is changing how marketing hands off leads to sales, and how/when sales teams get manually involved.

How can modern sales teams and especially sales leaders use better processes and tactics to optimize how AI is used as part of their salestech?

The #1 value proposition for using Pitchit is that it allows sales teams to change how and when their sales team needs to invest manual labor and human operations into the sales process. I’ll give you an example. We work with master agents of telecommunications companies like T-Mobile, AT&T, Verizon, Boost, etc. Historically, their sales team had to get manually involved by dialing every single lead as soon as the lead entered their CRM from an advertisement. The sales team had to call the lead, schedule callbacks if they didn’t answer, handle repetitive Q&A on pricing/availability/objection handling, and manually enter sales into their portal. Pitchit can handle everything right up to the deal closing conversation, without any human involvement, so now sales teams only have to manually get involved when a lead is in the “last mile” of the sales process aka “Closers”

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