Personal blog of Yzmir Ramirez

Cresicor, a consumer packaged goods trade management platform startup, raised $5.6 million in seed funding to further develop its tools for more accurate data and analytics.

The company, based remotely, focuses on small to midsize CPG companies, providing them with an automated way to manage their trade promotion, a process co-founder and CEO Alexander Whatley said is done primarily manually using spreadsheets.

Here’s what happens in a trade promotion: When a company wants to run a discount on one of their slower-selling items, the company has to spend money to do this — to have displays set up in a store or have that item on a certain shelf. If it works, more people will buy the item at the lower price point. Essentially, a trade promotion is the process of spending money to get more money in the future, Whatley told TechCrunch.

Figuring out all of the trade promotions is a complicated process, Whatley explained. Companies receive data feeds on the promotions from several different places, revenue data from retailers, accounting source data to show how many units were shipped and then maybe data directly from retailers. All of that has to be matched against the promotion.

“No API is bringing this data back to brands, so our software helps to automate and track these manual processes so companies can do analytics to see how the promotions are doing,” he added. “It also helps the finance team understand expenses, including which are valid and those that are not.”

What certain companies spend on trade promotions can represent their second-largest cost behind manufacturing, and companies often end up reinvesting between 20% and 30% of their revenue into trade promotions, Whatley said. This is a big market, representing untapped growth, especially with U.S. CPG sales topping $720 billion in 2020.

“You can see how messy the whole industry is, which is why we have a bright future and huge TAM,” he added. “With this new funding, we can target other parts of the P&L like supply chain and salaries. We also provide analytics for their strategy and where they should be spending it — which store, on which supply. By allocating resources the right way, companies typically see a 10% boost in sales as a result.”

Whatley started the company in 2017 with his brother, Daniel, Stuart Kennedy and Nikki McNeil while a Harvard undergrad. Since raising the funding back in February, the company has grown 2.5x in revenue, while employee headcount grew 4x over the past 12 months to 20.

Costanoa Ventures led the investment and was joined by Torch Capital and a group of angel investors including Fivestars CTO Matt Doka and Hu’s Kitchen CEO Mark Ramadan.

John Cowgill, partner at Costanoa, said though Cresicor raised a seed round, the company was already acquiring brands and capital before releasing a product and grew to almost a Series A company without any outside capital, saying it “blew me away.”

Cresicor is the “perfect example” of a company that Costanoa would get excited about — a vertical software company using data or machine learning to augment a pain point, Cowgill added.

“The CPG industry is in the middle of a rapid change where we see all of these emerging, digital native and mission-driven brands rapidly eating share from incumbents,” he added. “For the next generation of brands to compete, they have to win in trade promotion management. Cresicor’s opportunity to go beyond trade is significant. It is just a starting point to build a company that is the core enabler of great brands.”

The new funding will be used mainly to hire more talent in the areas of engineering and customer success so the company can hit its next benchmarks, Alexander Whatley said. He also intends to use the funding to acquire new brands and on software development. Cresicor boasts a list of customers including Perfect Snacks, Oatly and Hint Water.

The retail industry is valued at $5.5 trillion, and one-fifth of it is CPG, Whatley said. As a result, he has his eye on going after other verticals within CPG, like electronics and pet food, and then expanding into other areas.

“We are also going to work with enterprise companies — we see an opportunity to work with companies like P&G and General Mills, and we also want to build an ecosystem around trade promotion and launch into other profit and loss areas,” Whatley said.

While SaaS has become the default way to deliver software in 2021, it still takes a keen eye to find the companies that will grow into successful businesses, maybe even more so with so much competition. That’s why we’re bringing together three investors to discuss what they look for when they invest in SaaS startups.

For starters, we’ll have Sarah Guo, who has been a partner at Greylock since 2013 where she concentrates on AI, cybersecurity, infrastructure and the future of work — all in a SaaS context of course. Among her investments are Obsidian, Clubhouse and Awake. Her exits include Demisto, which Palo Alto acquired for $560 million in 2019 and Skyhigh Networks, which McAfee bought for $400 million in 2018.

Prior to joining Greylock, she worked for Goldman Sachs investing in growth-stage companies and advising SaaS companies like Dropbox and Workday.

Next we’ll have Kobie Fuller, a partner at Upfront Ventures, who looks at SaaS as well as AR and VR. Fuller has been at Upfront since 2016 when he joined after a three-year stint at Accel. He oversaw a pair of billion dollar exits while at Accel including ExactTarget to Salesforce for $2.5 billion and Oculus to Facebook for $2 billion. Upfront investments include Bevy, community building software, which recently got a $40 million investment with 20% of that coming from 25 Black investors.

Finally, we’ll have Casey Aylward, a principal at Costanoa Ventures where she concentrates on early-stage enterprise startups. Among her investments have been Aserto, Bigeye and Cyral. She tends to concentrate on developer tools. “My entire career so far has been focused on developers: whether it was building tools for developers, building software myself or now investing in enabling technologies for the next generation of technical users,” she wrote on her bio page.

This prestigious group will share their thoughts at TC Sessions: SaaS, a one-day virtual event that will examine the state of SaaS to help startup founders, developers and investors understand the state of play and what’s next. We hope you’ll join us.

The single-day event will take place 100% virtually on October 27 and will feature actionable advice, Q&A with some of SaaS’s biggest names and plenty of networking opportunities. Importantly, $75 Early Bird passes are now on sale. Book your passes today to save $100 before prices go up.

Jitsu, a graduate of the Y Combinator Summer 2020 cohort, is developing an open-source data integration platform that helps developers send data to a data warehouse. Today, the startup announced a $2 million seed investment.

Costanoa Ventures led the round with participation from Y Combintaor, The House Fund and SignalFire.

In addition to the open-source version of the software, the company has developed a hosted version that companies can pay to use, which shares the same name as the company. Peter Wysinski, Jitsu’s co-founder and CEO, says a good way to think about his company is an open-source Segment, the customer data integration company that was recently sold to Twilio for $3.2 billion.

But, he says, it goes beyond what Segment provides by allowing you to move all kinds of data, whether customer data, connected device data or other types. “If you look at the space in general, companies want more granularity. So let’s say for example, a couple years ago you wanted to sync just your transactions from QuickBooks to your data warehouse, now you want to capture every single sale at the point of sale. What Jitsu lets you do is capture essentially all of those events, all of those streams, and send them to your data warehouse,” Wysinski explained.

Among the data warehouses it currently supports are Amazon Redshift, Google BigQuery, PostGres and Snowflake.

The founders built the open-source project called EventNative to help solve problems they themselves were having moving data around at their previous jobs. After putting the open-source version on GitHub a few months ago, they quickly attained 1,000 stars, proving that they had delivered something that solved a common problem for data teams. They then built the hosted version, Jitsu, which went live a couple of weeks ago.

For now, the company is just the two co-founders, Wysinski and CTO Vladimir Klimontovich and couple of contract engineers, but they intend to do some preliminary hiring over the next year to grow the company, most likely adding engineers. As they begin to build out the startup, Wysinski says that being open source will help drive diversity and inclusion in their hiring.

“The goal is essentially to go after that open-source community and hire people from anywhere because engineers aren’t just […] one color or one race, they’re everywhere, and being open source, and especially being in a remote world, makes it so, so much simpler [to build a diverse workforce], and a lot of companies I feel are going down that road,” he said.

He says along that line, the plan is to be a fully remote company, even after the pandemic ends, as they hire from anywhere. The goal is to have quarterly offsite meetings to check in with employees, but do the majority of the work remotely.

Toro’s founders started at Uber helping monitor the data quality in the company’s vast data catalogs, and they wanted to put that experience to work for a more general audience. Today, the company announced a $4 million seed round.

The round was co-led by Costanoa Ventures and Point72 Ventures, with help from a number of individual investors.

Company co-founder and CEO Kyle Kirwan says the startup wanted to bring to data the kind of automated monitoring we have in applications performance monitoring products. Instead of getting an alert when the application is performing poorly, you would get an alert that there is an issue with the data.

“We’re building a monitoring platform that helps data teams find problems in their data content before that gets into dashboards and machine learning models and other places where problems in the data could cause a lot of damage,” Kirwan told TechCrunch.

When it comes to data, there are specific kinds of issues a product like Toro would be looking at. It might be a figure that falls outside of a specific dollar range that could be indicative of fraud, or it could be simply a mistake in how the data was labeled that is different from previous ways that could break a model.

The founders learned the lessons they used to build Toro while working on the data team at Uber. They had helped build tools there to find these kinds of problems, but in a way that was highly specific to Uber. When they started Toro, they needed to build a more general-purpose tool.

The product works by understanding what it’s looking at in terms of data, and what the normal thresholds are for a particular type of data. Anything that falls outside of the threshold for a particular data point would trigger an alert, and the data team would need to go to work to fix the problem.

Casey Aylward, vice president at Costanoa Ventures, likes the pedigree of this team and the problem it’s trying to solve. “Despite its importance, data quality has remained a challenge for many enterprise companies,” she said in a statement. She added, “[The co-founders] deep experience building several of Uber’s internal data tools makes them uniquely qualified to build the best solution.”

The company has been at this for just over a year and has been keeping it lean with four employees, including the two co-founders, but they do have plans to add a couple of data scientists in the coming year as they continue to build out the product.

Directly, a startup whose mission is to help build better customer service chatbots by using experts in specific areas to train them, has raised more funding as it opens up a new front to grow its business: APIs and a partner ecosystem that can now also tap into its expert network. Today Directly is announcing that it has added $11 million to close out its Series B at $51 million (it raised $20 million back in January of this year, and another $20 million as part of the Series B back in 2018).

The funding is coming from Triangle Peak Partners and Toba Capital, while its previous investors in the round included strategic backers Samsung NEXT and Microsoft’s M12 Ventures (who are both customers, alongside companies like Airbnb), as well as Industry Ventures, True Ventures, Costanoa Ventures and Northgate. (As we reported when covering the initial close, Directly’s valuation at that time was at $110 million post-money, and so this would likely put it at $120 million or higher, given how the business has expanded.)

While chatbots have now been around for years, a key focus in the tech world has been how to help them work better, after initial efforts saw so many disappointing results that it was fair to ask whether they were even worth the trouble.

Directly’s premise is that the most important part of getting a chatbot to work well is to make sure that it’s trained correctly, and its approach to that is very practical: find experts both to troubleshoot questions and provide answers.

As we’ve described before, its platform helps businesses identify and reach out to “experts” in the business or product in question, collect knowledge from them, and then fold that into a company’s AI to help train it and answer questions more accurately. It also looks at data input and output into those AI systems to figure out what is working, and what is not, and how to fix that, too.

The information is typically collected by way of question-and-answer sessions. Directly compensates experts both for submitting information as well as to pay out royalties when their knowledge has been put to use, “just as you would in traditional copyright licensing in music,” its co-founder Antony Brydon explained to me earlier this year.

It can take as little as 100 experts, but potentially many more, to train a system, depending on how much the information needs to be updated over time. (Directly’s work for Xbox, for example, used 1,000 experts but has to date answered millions of questions.)

Directly’s pitch to customers is that building a better chatbot can help deflect more questions from actual live agents (and subsequently cut operational costs for a business). It claims that customer contacts can be reduced by up to 80%, with customer satisfaction by up to 20%, as a result.

What’s interesting is that now Directly sees an opportunity in expanding that expert ecosystem to a wider group of partners, some of which might have previously been seen as competitors. (Not unlike Amazon’s AI powering a multitude of other businesses, some of which might also be in the market of selling the same services that Amazon does).

The partner ecosystem, as Directly calls it, use APIs to link into Directly’s platform. Meya, Percept.ai, and SmartAction — which themselves provide a range of customer service automation tools — are three of the first users.

“The team at Directly have quickly proven to be trusted and invaluable partners,” said Erik Kalviainen, CEO at Meya, in a statement. “As a result of our collaboration, Meya is now able to take advantage of a whole new set of capabilities that will enable us to deliver automated solutions both faster and with higher resolution rates, without customers needing to deploy significant internal resources. That’s a powerful advantage at a time when scale and efficiency are key to any successful customer support operation.”

The prospect of a bigger business funnel beyond even what Directly was pulling in itself is likely what attracted the most recent investment.

“Directly has established itself as a true leader in helping customers thrive during these turbulent economic times,” said Tyler Peterson, Partner at Triangle Peak Partners, in a statement. “There is little doubt that automation will play a tremendous role in the future of customer support, but Directly is realizing that potential today. Their platform enables businesses to strike just the right balance between automation and human support, helping them adopt AI-powered solutions in a way that is practical, accessible, and demonstrably effective.”

In January, Mike de la Cruz, who took over as CEO at the time of the funding announcement, said the company was gearing up for a larger Series C in 2021. It’s not clear how and if that will be impacted by the current state of the world. But in the meantime, as more organizations are looking for ways to connect with customers outside of channels that might require people to physically visit stores, or for employees to sit in call centres, it presents a huge opportunity for companies like this one.

“At its core, our business is about helping customer support leaders resolve customer issues with the right mix of automation and human support,” said de la Cruz in a statement. “It’s one thing to deliver a great product today, but we’re committed to ensuring that our customers have the solutions they need over the long term. That means constantly investing in our platform and expanding our capabilities, so that we can keep up with the rapid pace of technological change and an unpredictable economic landscape. These new partnerships and this latest expansion of our recent funding round have positioned us to do just that. We’re excited to be collaborating with our new partners, and very thankful to all of our investors for their support.”

Alation, a startup that helps crawl a company’s databases in order to build a data search catalog, announced a $50 million Series C investment today.

The round was led by Sapphire Ventures and Salesforce Ventures. Existing investors Costanoa Ventures, DCVC (Data Collective), Harmony Partners and Icon Ventures also participated. Today’s investment brings the total raised to $82 million, according to Crunchbase data.

The participation of Sapphire Ventures, originally launched by SAP, and Salesforce Ventures, the venture arm of Salesforce, is particularly telling. One of the issues these enterprise software companies face when they go inside large enterprises is helping customer’s access and understand data wherever it lives. It’s one of the reasons that Salesforce bought MuleSoft for $6.5 billion last year.

This is a problem that employees face, as well. It’s simply inefficient to query multiple databases manually, or to even know what databases exist inside a large organization. Alation uses out-of-the-box connectors to connect to common data sources like Oracle, Redshift, Teradata, Spark and Tableau to create a centralized data catalog.

With that catalog in place, employees can search just as they would with any enterprise search engine, with the notable difference that this tool is focused strictly on structured data inside of supported data sources.

The company goes beyond pure matching to find the data an employee is searching for. Company CEO and co-founder Satyen Sangani says they also use a method to analyze usage to display the most likely result. “What differentiates us in particular is that we look at the logs of how people are using that information,” he explained. This is analogous to how Google uses the PageRank algorithm to measure the popularity of a page based on the number of times people link to a page.

Alation catalog page. Screenshot: Alation

It is certainly not alone in the space, with competitors like Alteryx and Informatica, but Alation’s approach seems to be resonating. Sangani reports triple-digit growth four years running. The company has soared from 89 employees at the end of last year to around 200 today. It boasts 100 large enterprise customers in production, including names like BMW, Hilton, American Express and Salesforce (whose investment arm, Salesforce Ventures also helped lead today’s round).

As the company grows rapidly, Sangani says he wants the capital in place to help fuel the increasing interest. The size and scope of his customers means that he will need to hire not just engineers to keep developing the product and building new connectors, but customer support and sales and marketing. In all, he expects to add between 100 and 200 employees in the next year.

He also wants to continue building out partnerships. As an example, Teradata is an authorized reseller, and has helped sell the product in global markets where a startup like Alation might lack the resources to enter.

Based in Redwood City, Calif., the company launched in 2012 and released the first version of the product in 2014. Its most recent round prior to today was a $23 million Series B in 2017.