When it comes to innovating through data-driven business models, large industry incumbents often have an advantage. Their scale and history can provide them with massive data sets generated through customer interactions as well as internal activities. For startups there is often the chicken and egg problem of building a large enough customer base to generate actionable data that can drive product and service innovation.
A number of innovative small companies, however, are finding ways around this and creating business value though repurposing existing data that can be found in a variety of places. A creative approach to finding and combining often disparate sources of data allied with the drive and enthusiasm found in successful startups can be a winning combination, as these examples illustrate.
1. Data for city planning
San Francisco-based Populus is an emerging player in the smart city space and amalgamates data from a variety of ride-hailing, car and bike sharing as well as e-scooter operators to help city authorities better plan their traffic and parking strategies. It adds value through being an aggregator for these data sources and presenting it in formats that city planners can easily work with. As Populus builds its client base of city authorities and data providers, the company is able to offer insights to both sides of this market gained through the analysis of larger and richer data sets.
2. Harvesting the social web
In London, Black Swan is growing its reputation amongst large FMCG firms for offering up-to-the-minute insights into emerging consumer behaviour patterns. It does this by harvesting data from online forums, social media, product review sites and other online spaces and then using its AI software to spot trends. Danone, PepsiCo and McDonalds pay the company for these insights which often provide more accurate and timely data than relying on more traditional methods such as consumer panels and surveys. Black Swan’s main lesson for other startups is that much of the data they use is collected from external sources and it is their proprietary software that adds the value. It has never been easier to access massive amounts of data at zero or little cost.
3. Making the data fit
True Fit from Boston has found an interesting niche in the online fashion sector by offering shoe and apparel manufacturers and retailers access to sizing data. As clothing retail moves online and the ability of shoppers to try shoes and clothing on instore is reduced, there is a growing need for more precise fit and size data in the market. By collecting data from designers, its registered users as well as consumer surveys, True Fit offers a range of data services to the industry to improve the customer experience and reduce the number of returned items to ecommerce operators. Like Populus, the company acts as an aggregator of data which it collects from different stakeholders in the sector and adds value through its analysis and presentation. Since 2010, the company has raised $97 million in funding and is creating a highly defensible position in a rapidly growing market.
4. Marketing insights from WiFi
British-based Purple has found a way of extracting value from the data users provide when they log in to public WiFi networks in hotels, shops and other commercial locations. The data they capture from their login portal may contain dates of birth and personal interests as well as frequency of visits and movement within locations. Their value proposition to the location operators is based around delivering more personalised marketing campaigns and, in their own words, “transforming your guest WiFi network into a revenue generating tool for your business”. One of their clients, Pizza Express in the UK, has installed over 1024 WiFi access points across its 470 restaurants and used the data collected by Purple to drive downloads of its smartphone app.
5. Statistics for the rest of us
Finally, Statista from Germany has become a familiar name for anyone searching the web for statistical data. Since 2007 the company has built a registered user base of more than 1.5 million and receives up to 12 million visits a month. Working with data suppliers as well as harvesting public information from the web, Statista has built a successful subscription-based business model for customers that want low cost access to data across a wide range of sectors and technologies. Their repackaging of largely freely available data into user and search engine friendly chunks demonstrates the value of aggregation and presentation.
Some key lessons to be learned from these companies is that bigger data sets do not always equal market success. Finding creative ways to repurpose niche data and present it in ways that meets a market need can be a far more successful way of building a sustainable business model from which spin-off products and services can be launched.