Thanks for Visiting!

Register for free to get the full story.

Sign Up
Already have a Placer.ai account? Log In

Placer.ai Series C - Why Placer Raised $100M

by 
Noam Ben-Zvi
 on 
January 25, 2022
Placer.ai Series C - Why Placer Raised $100M

We, the founding team, always loved data - ideating around it, engineering with it, understanding the world better with it. 

But what captivated us most was imagining data products that can be used by tens of thousands of businesses across the world.

Among all the ideas and visions we bounced around before starting the company, one stood out for its simplicity and potential impact - building a ‘Physical Market Intelligence Platform’ to provide everyone in the offline world (a.k.a the ‘real world’) with aggregate insights for decision-making. Or in layman’s terms, “a dashboard to get instant insights for any place to understand its audience, surroundings, and competition”.

In 2016, the Placer founding team gathered in a basement and spent a weekend sketching out a plan to turn this idea into a massive world-class data company. 

Why did we get so excited?

  1. We loved using insight tools like SimilarWeb and App Annie that were made for the digital world.
  2. A massive market - 80-90% of spend is offline and is not going anywhere, anytime soon. We did not believe in the ‘retail apocalypse’ narrative.
  3. An industry ‘flying blind’ - this immense offline world has suffered from a lack of information critical to its decision-making.
  4. Data is especially critical for the physical world. The famous Facebook motto “move fast and break things” (which we practice at Placer) does not work well in the physical world. Brick & mortar decisions are costly and irreversible. It also takes a LONG time to understand you’ve made a mistake.
  5. Market Research is aggregated data - no need for any personal identifiable information (PII). This means we could build a privacy-first company, without PII data challenges.
  6. It’s a hard problem - which presents the opportunity to build something special. And in hindsight it’s been 10x harder than we thought!

Whiteboarding without customers or tech debt is fun!!!

The more paper we stuck to that basement wall, the bigger the vision became! Everything is possible with the stroke of a pen… 

But very quickly, we hit some glaring challenges:

  • The platform had to be about answering key business questions. But to generate the BEST reports that do so, there are 100s of relevant datasets that we MUST aggregate
  • The retail ecosystem is DIVERSE - retailers, CRE, CPG, travel, hotels, billboards are all unique worlds in and of themselves. Can we build a platform that reflects this? 
  • And…growing up in a “digital bubble” - the founding team knew VERY LITTLE about the retail world, its major players and how they work.

The best way to approach a big challenge is breaking it down into smaller ones. So we worked hard to define Phase 1 - focusing on building a product that (1) was centered around the mobile location analytics dataset and (2) generated reports tailored for CRE and retail

5 years and 5 funding rounds later, we’re FINALLY feeling “pretty good” about Phase 1: we launched a world-class mobile analytics product that’s used by over 1,000 customers, and thousands more are using our free products

But it’s also been “frustrating”  - we were always strapped for cash and resources. We’re yet to integrate most of the datasets we need; key reports for certain verticals remain in the product pipeline; and in terms of usability and workflow features, we still have a lot to do in order to create a truly comprehensive platform (vs “read only” status insights tool).

That’s why the $100M Series C funding we just announced is so momentous for me and the rest of the Placer team. It finally removes the shackles and equips us with the tools and materials we need for Phase 2 - rapidly building the full Placer.ai Market Intelligence Platform.

So let’s dive into what that means…

How does it work?

A Physical Market Intelligence Platform is a big data puzzle. Piecing it together - in a nutshell - consists of four phases:

  1. The Ingredients - identifying and assembling the data.
  2. Ingestion - processing and aggregating that information.
  3. Delivery - making it presentable and accessible.
  4. Customizations - every vertical is seemingly interested in very similar data, but with a different lens. This requires nuanced packaging around information density, terminology, order of reports, and 3rd party data-sets.
The Placer.ai Market Intelligence Platform
The Placer.ai Market Intelligence Platform

Ingredients

A vast amount of interconnected data is required to create a truly accurate and complete picture of what’s going on at a location. This data falls into two broad categories:

  • Point of interest (POI) data offering information on places such as a grocery store, retail centers and wider areas.
  • Geospatial data such as impactful events in the area, traffic data and future development projects.

Now consider all things you see going on in the world and imagine how POI and geospatial data can capture and quantify them…

Here’s a snippet:

We track dozens of data categories and thousands of datasets and vendors in order to identify new data that can help answer our customers’ questions.

  • Our product team draws on our customers’ feedback and wider market research to identify and triage the datasets we need to answer the questions. 
  • Our BD team lines up commercial partnerships with the data providers.
  • Our data analysts and scientists carry out a lengthy quality assessment process, which includes testing the data’s relevance, accuracy, data trust compliance, coverage, compatibility, recency, accessibility and alternatives.

This is 50% of our work and is a huge data challenge - but also great fun!

Among the real world visibility datasets

Through partnerships and our App Marketplace, we’ve recently integrated online reviews, credit card data, demographics, vehicle traffic volume, crime figures and planned construction into our platform. And we have lots more datasets in our pipeline: retail sales, property sales, financial data, leasing comparisons and climate data to name just a few.

Vehicle Traffic Volume
Crime
Planned Construction

Ingestion

If the data are the ingredients, then ingestion is the cooking. This includes complex data science processes:

  • Anonymization - eliminating personal identifiable information
  • Normalization - adapting the data’s various fields to fit Placer’s data model
  • Cleansing - ensuring that the data is as accurate and complete as possible
  • Enrichment - adding existing data layers to the ingested data, or extrapolating information from it
  • Tagging - associating the data with relevant POIs, industry categories, and so on to create meaningful insights.

Tagging data to POIs is a massive task. Placer’s POI database contains millions of entities: a commercial real estate asset in a customer’s portfolio; stores of a retailer’s chain or that hold a CPG brand’s products; a billboard used for out-of-home advertising; a downtown area being regenerated by a municipality or business improvement district. We geofence each one so data can be tagged to it.

But a much greater complexity than the volume of data-POI matching is the fact that our data structure is mutable - it changes. Stores, restaurants, strip malls and other POIs open, close, merge and move. Our physical environment is constantly changing. One of our platform’s standout attributes is that it always reflects historical change.

In practice, this means that, for each POI change, we not only adjust our data tagging but also re-tag 5 years of historical data to ensure any historical comparisons are “like with like”. This is a huge investment of resources on the part of our data science, devops and engineering teams - exponentially increasing our data management burden.

Delivery

To complete the cooking metaphor, after selecting ingredients (datasets) and cooking them (data ingestion), we then lay out a buffet-style feast of solutions for our users:

Basic Reports and Insights

The most basic level of the platform is converting the data into real-world constructs that can be understood by industry professionals: tables, charts, maps and other graphics displaying cross shopping, trade areas (below), cannibalization, risk analysis, visit frequency and so on.  

Solutions 

A key tenet of the Market Intelligence Platform is the approach that insights like those are often not the answer to the questions that our customers are looking for. Rather, they are just part of the explanation behind the answer. That means providing a comprehensive suite of Solutions SUPPORTED by insights, not just a library of uncontextualized insights. 

An excellent example of this is Void Analysis. A key question for retail real estate is “who is my ideal tenant?” While our platform offered important insights (such as retailers’ average monthly foot traffic and cannibalization) for reaching an answer, landlords were doing a lot of legwork. The Void Analysis tool we released late last year enables CRE professionals to instantly analyze thousands of potential tenants through automatically generated reports that include ranking according to our unique Relative Fit Score. This significantly improves the speed and scope of a search for new tenants.

Void Analysis - Who is the best fit for my vacancy?

We are now working on the many additional solutions like Void Analysis in our development pipeline - sales forecasting, site selection for retail chains, market selection, market change reports, product optimization for CPG to name a few.

Placer REST API

Programmatic Access & Exploration Tools

To be truly useful, solutions must also be delivered in a way that fits various users’ workflows. A dashboard is a good start, but a full platform must offer a range of access points. This means data feeds, REST APIs, and other methods of programmatic access.

We’ll also add to that a rich layer of data exploration tools such as GIS, templates, graph builders, pivot table functionality and advanced entity search. This will provide users with maximum flexibility in how they explore and visualize our data.

The lion’s share of the work is still ahead of us here - more widgets, third party integrations, report generators, scheduled intelligence reports and alerts, and much more.

COVID-19 Economic Recovery Dashboard

Vertical Specific Customizable Dashboards

The platform’s user interface must be fully customized to fit the needs of its different user types across verticals AND within companies (business users, data scientists, data analysts, third party users). An example of how we’ve begun to do this is a portfolio overview section for CRE analysts to rapidly scan properties’ performance metrics. Another is our COVID-19 Recovery Dashboard, particularly used by civic organizations to assess the impact of the pandemic on local economic areas.

The Anchor: Placer's CRE Executive Intelligence Report

Research

As we presented “just data”, we quickly realized some customers were looking for humans to add a “research layer” and context around the data. So an analytical research team has become part of the product. They capture and present key market intelligence, respond to the latest industry trends and customer interests. “The Anchor”, a weekly CRE executive intelligence report launched last September, has now become an inbox staple for many of our customers.

Let’s build it!

To our current understanding, we’re just “5%” of the way to our Market Intelligence Platform vision. The remaining 95% will be built by scaling POI coverage, datasets, answering more questions and developing the other core components of the platform.

So our focus now is on ramping up the velocity of this development. And to do that, we need even more of the world’s best talent across the company. 

So, during 2022, we will use our new capital to double the size of our engineering team and significantly expand the data at our disposal. In parallel, we will also channel more resources to supporting our customers and contributing to industry understanding through our analytical research department and educational content. 

Placer.ai is committed to transforming the way real-world businesses make decisions. And we don’t want to waste any time going about it.

Get 3 brand & industry
breakdowns every week

Subscribe to the newsletter

Great! Prepare your inbox for data-driven insights...
Oops! Something went wrong while submitting the form.

Get a Demo

Please enter your first name
Please enter your last name
Please provide a valid email
Please enter your email
Please enter company name

Thanks for reaching out!

One of our experts will be in touch soon

Try Placer.ai Free
Oops! Something went wrong while submitting the form.
The CAVA Craze: A Location Intelligence Perspective on the Mediterranean Marvel
How Will Primark’s US Expansion Impact Target?
All Eyes on Eyewear
Northwestern U.S. Grocery Dive
Return of the Lunch: Salad Chains Are Thriving
Retail Media Networks – Off the Beaten Track
Bet Your Bottom Dollar: Discount and Dollar Stores Drive Foot Traffic
Ulta & Lululemon: Discretionary Spending On The Up
The Score After Q1: Sporting Goods Chains
Who Uses NYC Airports: Biting Into The Big Apple’s Main Transport Hubs
Off Price: Strength in The Face of Retail Challenges
Visits Improve for Home Improvement
Walmart, Target & Wholesalers in Q1 2023 – The Return of Mission-Driven Shopping?
Department Store Roundup: Q1 2023
Placer.ai Office Index: April 2023 Recap
Placer.ai Mall Index, April 2023 – A Rebound on the Horizon?
How Will Bed Bath & Beyond’s Bankruptcy Impact the Retail Space?
Buffet Restaurants: Filling Up on Foot Traffic
Thrift Stores: Vintage Visits Drive New Age in Apparel
The Windy City: A Hub of Post-Pandemic Opportunity
Diving into Dining Traffic - Q1 2023
Bring On The Joe
A Dollar (or more) For Your Thoughts: Five Below and pOpshelf
Dining Out With The Cheesecake Factory
Retail Foot Traffic Recap – March 2023
Digging Into 2023: McDonald’s and Chipotle Update
Placer.ai Office Index: March 2023 Recap
How Did Key Retail Categories Perform in Q1 2023?
Northeastern USA Grocery Dive
Movie Theaters Storylines for 2023
Ollie's Bargain Outlet: Discounters are Evolving
Leveraging Brick-and-Mortar Retail in 2023
America’s Evolving Work Patterns: A Deep-Dive into New York and Chicago
Placer.ai Mall Index March 2023
Tuning Into Record Stores
Five Franchises To Watch in 2023
What’s Next For Domestic Tourism?
It’s Showtime! Movie Theaters in the Spotlight
5 Limited Time Offers (LTOs) Driving Restaurant Traffic
Department Store Deep-Dive: Belk
Regional Grocery Chains Staying Ahead of the Competition
Five Chains that Rightsized for Success
Unlocking the Potential of Offline Retail Media Networks
Dining Out With Darden
What’s in Store for Self-Storage?
Nike & lululemon Update: Strong Performance Amid Expansion Plans
Many Ways to Win: Midwest Grocery Deep Dive
Retail, Reinvented: The Rise of the Pop-Up Shop
Navigating a New Normal in Business Travel & Commutes
Placer.ai Office Index: February 2023 Recap
Retail Categories Staying Strong in Volatile Environment
Ulta Beauty: Poised for Success into 2023
Placer.ai Mall Index February 2023: Reasons for Continued Optimism
Catching Up With DICK’s & Hibbett
The Miami-Dade Arena: An Advertising Slam Dunk
Car Washes Revving Up Visits
Tuesday Morning and Sunrises in Home Furnishing
Dining & Valentine’s Day Recap
2023: The Year of the Discount Store
Aldi’s Success Highlights Growing Demand for Value Groceries
5 Retail & Service Categories Holding onto Pandemic Gains in 2023
Visitor Insights from Super Bowl 2023
2023 First Look: Home Improvement Update
How Are Target, Walmart, and Wholesale Clubs Faring in 2023?
Department Store Deep-Dive: Nordstrom
Off-Price: Taking Off in Uncertain Times
Checking in On Middle-Class Hubs
Who Attends the Super Bowl?
Placer.ai Office Index: January 2023 Recap
Focusing On Fitness: Q4 and January Recap
Placer.ai Mall Index: January 2023 – Returning Mall Normalcy?
Location Intelligence Insights Into Concert Attendance
Winning Dining Strategies for 2023
In-N-Out Burger: What to Expect as the Brand Moves East
Location Intelligence Breakdown: Coffee Caps-Off 2022
Digitally Native Brands Lean Into Brick & Mortar
Washington, D.C. Population Changes & Migration Trends
A Location Intelligence Perspective on Macy’s Rightsizing
Amazon-Powered Shopping: The Future of Brick-and-Mortar Grocery?
Cold Weather, Hot Visits: Diving into Winter Resorts
Wawa and 7-Eleven: Leaning Into the “Slurpee Effect”
2022 and Beyond: Catching Up With McDonald’s & Chipotle
Let’s Have Some Fun! Going Out Is In
Placer.ai’s Q4 2022 Quarterly Index
Placer.ai Adds Industry Executives to Leadership Team To Drive Company's Next Phase of Growth
5 Emerging Retail Formats: 2023’s Brick-and-Mortar Evolution
Grocery Update: Zooming in on the Lone Star State
2022 Office Recap: The Year of the TGIF Work Week
What Lies Ahead for Brick-and-Mortar Luxury in 2023
Placer.ai Mall Indexes: December 2022 Recap
Looking Back on 2022’s Holiday Shopping Season
Post-Pandemic Migration Trends in New York
Top Retailers for 2023
The Live Sports Advertising Opportunity
Domestic Migration to the Mountain States: Small Shifts with Big Implications
New Year, New Food: 5 Dining Trends For 2023
Announcing Placer.ai’s COVID RECOVERY DASHBOARD
This is Why Shop-in-Shops Are Everywhere
Super Saturday 2022 Recap
The San Francisco Shift