For decades, awareness and familiarity, more than anything else, drove what consumers bought and where they shopped. They stayed at a Hilton over a small, but exceptional, boutique hotel because they knew what to expect with the chain. They drove 30 minutes to a Home Depot to find a particular tool instead of shopping at an independent hardware store because they knew it would be in stock.
That lack of information — the inability for a consumer to know what was around the corner — shaped the way marketers and businesses thought of the traditional purchase funnel, pushing many to invest heavily in branding campaigns aimed exclusively at generating awareness and familiarity with a given brand. In a world in which information is finite and often inaccessible, the ability for a business to be top of mind — to carve out a little spot in a consumer’s memory — was a powerful competitive advantage, and one that drove the way businesses sold goods and services to local consumers.
However, thanks to two developments — the rapid adoptionsf mobile devices by consumers and the emergence of inexpensive cloud-based operations software —that’s changing. A group of technology companies are creating systems to answer three key questions consumers might have about businesses — “Who are they?” (identity); “What do they sell?” (inventory) and “Will I like what they sell?” (verification).
It’s a development that could dramatically change consumer behavior in local markets, and impact over $4.4 trillion in sales in the U.S. alone. When consumers know what the hardware store has in stock or whether the small restaurant next door serves good food, the market enters what’s called a “state of perfect information.” When that happens, the rules of the game — both for consumers and the businesses trying to sell to them, change as well.
Brick-and-mortar businesses fail constantly. Some close their doors for good; others change their name or switch locations in search of a second chance. In Silicon Valley speak, they pivot. The constant changing and switching on Main Street has vexed the local data ecosystem for years, yielding a mature product that remains fraught with inaccuracies.
It’s not a new problem. The industry in the United States, which for years has been dominated by data providers like Acxiom, InfoGroup and Neustar, largely focuses on the same business listing data used in yellow books decades ago. But instead of going door-to-door, these data companies gather information from a number of sources — everything from scraping websites to licensed third-party data — then merge and weight each each data source, programmatically deciding which data are most likely correct for each field.
However, that’s starting to change. As mobile search plays increasingly important role in consumers decision-making locally, there’s an economic rational for business to ensure that the information about their business on the web is correct. Subsequently, startups like Yext, SinglePlatform, and Locu have found success building distribution networks that allow businesses to publish and manage their own information across the web.
However, that model is largely built for data that stays put. Business do not often move or change their name, but when they do, a week or so delay doesn’t break the bank. That’s not the case with inventory data however, which requires a degree of automation that aggregated, user- or merchant-generated systems simply cannot support.
Inventory search is maybe online’s starkest advantage over local markets, as attempts to aggregate local inventory over the past few years have largely failed. Milo, a local product search startup, sold to eBay in 2008, but it’s largely remained out of the hands of mainstream consumers. Meanwhile, companies like Retailigence, have built inventory datasets, but the information is predominately used to help marketers include nearby product information in mobile ads.
A large part of the problem rests in the systems which local businesses use to manage their back-office operations. These systems have largely remained offline, relegated to legacy tools like pen and paper or silo-ed in digital products not built for the web. However, cloud technology has dramatically reduced the cost of building and supporting point-of-sale systems, allowing companies like Square and Shopkeep to bring enterprise technology to a segment of small retailers and service providers, which may have traditionally been priced out of the market.
In many ways, it’s a phenomenon that’s hitting the service industry faster than retail. Startups that build software for small service businesses often compete with a much smaller legacy business systems industry than their retail or restaurant counterparts that face more widely adopted point-of-sale (POS) systems. Consequently, services-oriented business management systems like Booker, which help businesses publish and manage their service and scheduling online, have seen more rapid growth than their counterparts that focus on retail POS.
Maybe the most valuable layer in the local data ecosystem today, verification information — the content and data that helps consumers understand quality — is one area where local tech has kept up with its online counterparts. And for companies like Yelp, which have developed the necessary offline communities to generate reviews at a meaningful scale, the value of this information has begin to reveal itself. Shares of the review company have tripled over the past 12 months, boosting its valuation to well over $5 billion, as of the time of this writing.
Social recommendation products from Facebook and Twitter could threaten Yelp’s position in the market, but the longer-term threat to Yelp comes from a more data-driven approach. As mobile positioning and battery-life improves, and devices can persistently track consumer movements, there’s an opportunity over the next decade for companies to use those data to facilitate discovery similar to Amazon recommendations. Content isn’t going anywhere soon; but data will have its day.
Steven Jacobs is Street Fight’s deputy editor.
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