Sequoia leads $10M round for home improvement negotiator Setter

You probably don’t know how much it should cost to get your home’s windows washed, yard landscaped or countertops replaced. But Setter does. The startup pairs you with a home improvement concierge familiar with all the vendors, prices and common screwups that plague these jobs. Setter finds the best contractors across handiwork, plumbing, electrical, carpentry and more. It researches options, negotiates a bulk rate and, with its added markup, you pay a competitive price with none of the hassle.

One of the most reliable startup investing strategies is looking at where people spend a ton of money but hate the experience. That makes home improvement a prime target for disruption, and attracted a $10 million Series A round for Setter co-led by Sequoia Capital and NFX. “The main issue is that contractors and homeowners speak different languages,” Setter co-founder and CEO Guillaume Laliberté tells me, “which results in unclear scopes of work, frustrated homeowners who don’t know enough to set up the contractors for success, and frustrated contractors who have to come back multiple times.”

Setter is now available in Toronto and San Francisco, with seven-plus jobs booked per customer per year costing an average of over $500 each, with 70 percent repeat customers. With the fresh cash, it can grow into a household name in those cities, expand to new markets and hire up to build new products for clients and contractors.

I asked Laliberté why he cared to start Setter, and he told me “because human lives are made better when you can make essential human activities invisible.” Growing up, his mom wouldn’t let him buy video games or watch TV so he taught himself to code his own games and build his own toys. “I’d saved money to fix consoles and resell them, make beautiful foam swords for real live-action games, buy and resell headphones — anything that people around me wanted really!” he recalls, teaching him the value of taking the work out of other people’s lives.

Meanwhile, his co-founder David Steckel was building high-end homes for the wealthy when he discovered they often had ‘home managers’ that everyone would want but couldn’t afford. What if a startup let multiple homeowners share a manager? Laliberté says Steckel describes it as “I kid you not, the clouds parted, rays of sunlight began to shine through and angels started to sing.” Four days after getting the pitch from Steckel, Laliberté was moving to Toronto to co-found Setter.

Users fire up the app, browse a list of common services, get connected to a concierge over chat and tell them about their home maintenance needs while sending photos if necessary. The concierge then scours the best vendors and communicates the job in detail so things get done right the first time, on time. They come back in a few minutes with either a full price quote, or a diagnostic quote that gets refined after an in-home visit. Customers can schedule visits through the app, and stay in touch with their concierge to make sure everything is completed to their specifications.

The follow-through is what sets Setter apart from directory-style services like Yelp or Thumbtack . “Other companies either take your request and assign it to the next available contractor or simply share a list of available contractors and you need to complete everything yourself,” a Setter spokesperson tells me. They might start the job quicker, but you don’t always get exactly what you want. Everyone in the space will have to compete to source the best pros.

Though potentially less scalable than Thumbtack’s leaner approach, Setter is hoping for better retention as customers shift off of the Yellow Pages and random web searches. Thumbtack rocketed to a $1.2 billion valuation and had raised $273 million by 2015, some from Sequoia (presenting a curious potential conflict of interest). That same ascent may have lined up the investors behind Setter’s $2 million seed round from Sequoia, Hustle Fund and Avichal Garg last year. Today’s $10 million Series A also included Hustle Fund and Maple VC. 

The toughest challenge for Setter will be changing the status quo for how people shop for home improvement away from ruthless bargain hunting. It will have to educate users about the pitfalls and potential long-term costs of getting slapdash service. If Laliberté wants to fulfill his childhood mission, he’ll have to figure out how to make homeowners value satisfaction over the lowest sticker price.

Edo raises $12M to measure TV ad effectiveness

Edo, an ad analytics startup founded by Daniel Nadler and actor Edward Norton, announced today that it has raised $12 million in Series A funding.

Nadler and Norton have both had startup success before — Nadler co-founded and led Kensho, which S&P Global acquired for $550 million. Norton invested in Kensho and co-founded CrowdRise, which was acquired by GoFundMe.

Even so, ad analytics might seem like an arcane industry for an actor/filmmaker to want to tackle. However, Norton said he was actually the one to convince Nadler that it was worth starting the company, and he argued that this is an important topic to both of them as creators. (Nadler’s a poet.)

“Movie studios and publishers, they take risks on talent, on creative people like us,” Norton said. “We want them to do well … The better they do with the dollars they spend, the less risk averse they become.”

Nadler and Norton recruited Kevin Krim, the former head of digital at CNBC, to serve as Edo’s CEO.

Krim explained that while linear TV advertising still accounts for the majority of ad budgets, the effectiveness of those ads is still measured using old-fashioned “survey-based methodologies.” There are other measurement companies looking online; Norton said they’re focused on social media sentiment and other “weak proxies” for consumer behavior.

In contrast, Edo pulls data from sources like search engines and content sites where people are doing research before making a purchase. By applying data science, Krim said, “We basically can measure the change in consumer engagement, the behaviors that are indicative of intent. We can measure the change in consumer behavior for every ad.”

In fact, Edo says that since its founding in 2015, it has created a database of 47 million ad airings, so advertisers can see not just their own ad performance, but also that of their competitors. This allows advertisers to adjust their campaigns based on consumer engagement — Krim said that in some cases, advertisers will receive the overnight data and then adjust their ad rotation for that very night.

As for the Series A, it was led by Breyer Capital. (Jim Breyer has backed everything from Facebook to Etsy to Marvel.) Vista Equity co-founders Robert Smith and Brian Sheth participated in the round, as did WGI Group.

“For more than a decade I’ve watched the data science talent arbitrage transform industries from finance to defense, from transportation to commerce,” Breyer said in the funding announcement. “We needed someone to bring these capabilities to bear on the systemic inefficiencies and methodological shortcomings of measurement and analytics in media and advertising.”

On the customer side, Edo is already working with ESPN, Turner, NBCUniversal and Warner Bros. I wondered whether some of the TV networks might have been worried about what Edo would reveal about their ads, but Norton said the opposite was true.

“I don’t sense that they in any way have trepidation that we’re going to pull their pants down — quite the opposite,” he said. “They are absolutely thrilled with our ability to help burnish and validate their assertions about the strength of what they’re offering.”

Rockset launches out of stealth with $21.5 M investment

Rockset, a startup that came out of stealth today, announced $21.5M in previous funding and the launch of its new data platform that is designed to simplify much of the processing to get to querying and application building faster.

As for the funding, it includes $3 million in seed money they got when they started the company, and a more recent $18.5 million Series A, which was led by Sequoia with participation from Greylock.

Jerry Chen, who is a partner at Greylock sees a team that understands the needs of modern developers and data scientists, one that was born in the cloud and can handle a lot of the activities that data scientists have traditionally had to handle manually. “Rockset can ingest any data from anywhere and let developers and data scientists query it using standard SQL. No pipelines. No glue. Just real time operational apps,” he said.

Company co-founder and CEO Venkat Venkataramani is a former Facebook engineer where he learned a bit about processing data at scale. He wanted to start a company that would help data scientists get to insights more quickly.

Data typically requires a lot of massaging before data scientists and developers can make use of it and Rockset has been designed to bypass much of that hard work that can take days, weeks or even months to complete.

“We’re building out our service with innovative architecture and unique capabilities that allows full-featured fast SQL directly on raw data. And we’re offering this as a service. So developers and data scientists can go from useful data in any shape, any form to useful applications in a matter of minutes. And it would take months today,” Venkataramani explained.

To do this you simply connect your data set wherever it lives to your AWS account and Rockset deals with the data ingestion, building the schema, cleaning the data, everything. It also makes sure you have the right amount of infrastructure to manage the level of data you are working with. In other words, it can potentially simplify highly complex data processing tasks to start working with the raw data almost immediately using SQL queries.

To achieve the speed, Venkataramani says they use a number of indexing techniques. “Our indexing technology essentially tries to bring the best of search engines and columnar databases into one. When we index the data, we build more than one type of index behind the scenes so that a wide spectrum of pre-processing can be automatically fast out of the box,” he said. That takes the burden of processing and building data pipelines off of the user.

The company was founded in 2016. Chen and Sequoia partners Mike Vernal joined the Rockset board under the terms of the Series A funding, which closed last August.