In this edition of Localogy’s Local Radar series, we examine SMB sales automation player Openmart.
Openmart wants to tackle the most vexing and longstanding challenge of the multi-billion dollar SMB Saas sector: sales. As Localogy readers know, the market is fragmented, varied, time-starved, and tech-challenged. This makes the process of selling to them onerous… if you can even get in front of them.
This phenomenon continues to challenge established players in the local media, marketing, and commerce worlds, not to mention unsuspecting new blood. The latter often enters the SMB Saas space with opportunistic visions of its underserved status and long-tail economics… then hits a brick wall.
Openmart founder Kathryn Wu was one of those players, and the challenges she faced drove her to launch Openmart. Specifically, she started a milk-tea side business called OhTea while working as a product engineer at Pinterest. She quickly stumbled when selling it to local grocers and specialty shops.
The issue wasn’t just the typical SMB challenges noted above (tech illiteracy, etc), but even getting to step one: contacting them. Things like assembling a list of sales targets and the right points of contact held her from even getting to the starting line. Ultimately, this caused paralysis… and OhTea’s demise.
Shelf Space
Given those challenges, Openmart emerged from Y-Combinator’s W24 cohort as a sales automation tool for the SMB market. Helping SaaS players find the right SMB contacts, you can think of it like CrunchBase or LinkedIn Sales Navigator for SMBs, assembling valued data that’s otherwise scattered.
And like every other startup launching today, Openmart employs a fair share of AI. It claims to apply machine learning to elevate the traditional process of scraping public data, including review sites and maps. This engenders a searchable taxonomy of business details (e.g., do they have a liquor license?)
The use case is broad, says the company, but one target persona is large enterprises that sell to SMBs. For example, CPGs that want shelf space at local retailers could use Openmart’s info to find and contact the right decision-makers with less friction. This saves time and lets them cover more ground.
To be fair, Openmart isn’t the only player to do this, nor to have scraping capabilities. Players like Vsplash and other SMB databases have done similar, while Places Scout has venerable web scraping and indexing tech. Players like Soci, Yext, and Uberall meanwhile have various flavors of local listings data.
Defense & Dog Food
A few thoughts emerge from all the above, and from Openmart’s concept broadly. First, the idea has potential because it scratches a real itch for anyone selling things to SMBs. If nothing else, it saves them time and headaches. That time equals money or, as noted, lets them run faster and cover more ground.
But it’s not all good news. One question that arises is what differentiating factors – technical or otherwise – do Wu and her co-founder Richard He bring to the table. The pair met as interns at Pinterest and have respectable product engineering chops, but do they have ample perspective on SMB market dynamics?
Another question involves barriers to entry and defensibility. Given that the technologies at play seem to include web scraping and AI, it’s a question of how much proprietary deep tech is at work, and how much rigor would be involved in replicating it. We’d need a closer look under the hood to answer that.
The above questions are meant to be speculative rather than disparaging. We’ll be watching for progress and demand signals. Meanwhile, Openmart has a handful of Fortune 500 customers and raised $2.75 million in seed funding. And as it grows, it can dogfood its own tech in its business development efforts.
