Keeping Brick & Mortar Relevant in an Online World: An Interview with Haystack
Neustar had a chance to catch up with another of our amazing distribution partners for Neustar Localeze. Fred Pfeiffer, Account Executive at Neustar, interviewed Haystack co-creator Rohit Gupta, a former analyst and trader for Citadel. Gupta created Haystack along with Ben Dean, former Chief Analyst with New York City Mayor Michael Bloomberg’s Office of Data Analytics.
Fred: Can you tell us a bit about Haystack and the idea behind why you created this business?
Rohit: Sure, the basic idea behind Haystack is that shopping right now in physical store locations can be a difficult and somewhat painful process. And a lot of that pain is due to data issues, like missing product details or inaccuracy in stock information. There is a lot of helpful data like this that is missing from the physical world of retail or it’s fragmented or incomplete. So we are trying to bring some of the big benefits of e-commerce and the Amazon-type world that we live in, to the brick and mortar stores.
‘I can’t find x’ is a common problem. ‘I couldn’t find a cooking ingredient while we were in the middle of cooking’, ‘I just moved in and couldn’t find a shower curtain’, and so on. These are easily solvable problems. Because of this, we thought it was important to create an online marketplace for retail — to make it easier for consumers to shop and to browse store shelves and to allow brick and mortar stores to compete in the online world.
Fred: How are you getting the word out about Haystack and promoting your own business?
Rohit: Well, we’ve had our heads down in product development for awhile. But as we are launching now, we’ll get the word out through traditional marketing, email marketing, things like that in the medium term. We also have a few different partnership options we are exploring. One is with small business associations and local business improvement districts. Another is potentially partnering with delivery services. The last-mile delivery market is very active, and we’re hoping to harness some of that with a data engine for the back end that would allow for last-mile delivery from local stores.
An aspect that is unique to us in terms of going to market is that, there is an enormous number of people who are searching for products near them and getting bad results on search engines when they search for “batteries near me” or “phone chargers near me”, etc, and it’s evident there is a need for our service. We believe this will be a great way to target and pick up users.
Fred: Are you able to track user insights?
Rohit: We are tracking and trying to understand what people are searching and where, so we can understand the specific categories that are important. We look at things like — are they searching mainly groceries? Or for hardware? We’re also trying to understand — do people need stuff at the granularity level of a shopping list like (AAA) batteries? Or are they pasting in the full SKU from Amazon right into our site? We are trying to understand these dimensions so we know where to focus.
While we are still in the pretty early stages of getting this insight, there are some clear trends. For instance, consumer packaged goods and hardware are definitely something people need and especially last-minute. As we acquire more users, we’re excited to see what we will learn with a much bigger search volume.
One thing we think a lot about is how to track real conversion — do they show up to the retailer and complete the purchase? We know this happens anecdotally when we talk to people, but we want to figure out how to track that attribution, and there are attribution services available out there, so that is something we are exploring.
Fred: How are you utilizing the Localeze data?
Rohit: So that’s really the backbone of our brick and mortar retailer data. Local data is very difficult, as you know, so we need to make sure that a place exists and that the basic data about that place is correct — like name, website, phone number, etc. We also want to understand in as much detail as possible what kind of store they are (by using) the other associated data like categorization that Localeze provides. This is especially important for us as we do some predictive analytics around what we think a store might carry.
Fred: What’s important to you from a data standpoint?
Rohit: From a user perspective, it’s worse if a place shows up that doesn’t exist vs. a place that does exist but is missing from results. It’s a big pain to show up somewhere and the place does not exist. So one of the main things is tracking businesses that have closed.
Fred: Are there any particular verticals that are most important to you?
Rohit: For now, hardware is pretty important, as well as grocery stores. There’s a lot of reasons people look at these verticals when they do their shopping. With groceries, often people want to shop in person or they buy last-minute for cooking, or you might need some random thing and want to check out if it’s available nearby before wasting trips to different stores. And for hardware it’s a similar story, where you might need a little bit of browsing because certain parts won’t work or are super specific. You might need a refrigerator filter and you don’t want to get the wrong one. Even with the details available online, it’s easy to make errors. So those sorts of verticals are particularly useful to people. People just don’t know what is available at the retail locations around them, particularly when it's not a routine purchase.
Fred: Are there any geographic areas that are of specific interest to you?
Rohit: Right now we’ve focused on New York City. Urban areas are generally more important to us because of the density of brick and mortar retailers and the number of people that shop there.
Neustar wants to thank Rohit for giving us a behind-the-scenes look at www.searchhaystack.com. It’s easy to see how Haystack will play a key role in improving local shopping for consumers and give brick and mortar retailers a way to stay in the game. You can read more about Haystack in this case study.