Marketing challenges with the 99%: SMEs


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“No one sells to SMEs, there are too many of them.”

Yogi Berra’s insights into popular restaurants could also apply to selling to small businesses. There are simply too many. Indeed, according to US Small Business Administration Advocacy Office, in 2021, there were 32.5 million small businesses. That’s 99.9% of all businesses. Most marketers focus on selling to the 0.1% of large organizations, generally categorized as those with more than 500 employees. The SBA estimated in 2020 that there were 20,139 large companies in the United States.

Small businesses employ 61 million people, or 46.8% of the workforce in the United States. So there is a good chance that you are one of them. They represent 97.5% of all exporters totaling $473 billion in 2020. Small businesses are important to the economy as an engine of economic growth and a mainstay of employment.

So why aren’t marketers targeting them more often, almost exclusively in fact? Because it’s hard to know who they are. The data does not exist, or if it does, it is incomplete or out of date. Let’s see why we focused so narrowly on the 0.1% of organizations.

SMEs keep changing

Small businesses have been hit particularly hard by the COVID-19 pandemic, with Black-owned businesses three times more likely to see a decline in business activity. Between March 2019 and 2020, small businesses accounted for 909,808 openings and 843,229 closings. That’s a lot of change.

The life of an SME can be short according to the SBA: “From 1994 to 2018, on average 67.6% of new employer establishments survived at least two years. During the same period, the five-year survival rate was 48.8%, the 10-year survival rate was 33.6%, and the 15-year survival rate was 25.7%.

Information about an SME has a short half-life of relevance because businesses themselves do not last.

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SMEs are silent

Public companies are, by nature, public about their contact details. They’re large, easy to identify, don’t change quickly, and release a range of measurements. Small businesses don’t do that – they only leave a small footprint. You might find reviews on Yelp, but they don’t advertise their audited accounts, diversity, equity, and inclusion (DEI) metrics, or other important milestones. The CEO could change, and it would be hard for the world to know.

From a marketing perspective, this is a challenge when it comes to building a persona and targeting specific segments. How do you know if this business is even in your target market? We need the equivalent of the James Webb Space Telescope to accurately pick up signals about SMEs.

SMEs are diverse

SMBs may be unified by their relatively small number of employees, but that’s where the similarities end. They have evolved to meet the needs of a hodgepodge of market niches ranging from the local florist to the metal shop that makes custom stair railings to asbestos removal specialists. The standard NAIC (National Association of Insurance Commissioners) or SIC (Standard Industrial Classification) codes that classify companies into groups such as mining, construction and manufacturing are still extremely broad.

From a marketing perspective, for B2SMB companies, this means a lot of wasted expense and effort. It’s easier to hunt the big game on the organizational plains than to figure out who those SMEs are, even if they might buy your product.

It also means that marketers want a variety of information to create a profile of each SME. Simple revenue and employee data will not suffice. They may need details on the business model (is it a franchise?), local retail store traffic, online reviews, regional weather, average community income within 8 miles km, the presence on social networks or the ethnicity of the possession. In fact, each marketer may want a different set of external data signals for the next one. This is a challenge for data providers who must organize and then sell this information.

Related article: Intent data and the gap between sales and marketing

Gold hidden in plain sight

It’s not just the challenge of corporate long-tail marketing. This queue represents 99.9% of the companies. It’s actually a problem of economics. For traditional data providers, it is advantageous to provide firmographic data on public companies to companies, large and small, that want to reach them.

Fast-changing, multivariate, large-scale, hard-to-reach data on SMEs looks less appealing compared to slower, more stereotyped, defined, and publicly available data on businesses. So it just wasn’t available and marketers had to look elsewhere.

But there are signs that things are starting to change.

First, SMEs themselves are starting to create a larger data wake and are becoming more transparent. They have websites, their staff are profiled on LinkedIn, government entities are making information available in a more accessible and timely way, and directories are being organized to profile small businesses that were previously locked in door stops like Pages. Yellows.

Second, advances in Big Data and ML mean that datasets can be cleaned, labeled, and presented in a more accessible format. Collection, cleanup, and storage costs are falling through automation, public cloud, and data storage improvements.

Third, on the demand side, the value of this data increases. Beyond the marketing use case, SMB data is now being deployed by a wide variety of companies to develop new products for them. Many new fintech companies are designing payment, lending, and insurance offerings specifically for SMEs. And, they can do this because they have access to a wide range of alternative external data for SMEs, beyond their address, their turnover and the number of employees, helping them to identify the right target or to assess credit risk.

For example, insurance companies create plans for SMEs. The risk profile of a gas station is very different from that of a hair salon, even though they may have similar revenues and number of employees.

Or take another sector, banking. According to the SBA, in 2019, reporting banks extended $87.1 billion in loans to U.S. businesses with revenues of $1 million or less. These are high risk loans and open to fraud. Better information about these start-ups can reduce this – a fake business is unlikely to have significant web traffic or strong social media engagement, for example, so this is useful data for fraud prevention. Suddenly, the data economy of SMEs has improved.

Thanks to the information available on SMEs, small and medium-sized enterprises will be better understood. They will find new suppliers, customers and partners. They will be offered more personalized products tailored to their needs and budget. Historically, they have been misunderstood or ignored. All of that could soon change, which is great for 99.9% of American businesses.

Ajay Khanna is CMO at Explorium, the automated external data platform for advanced analytics and machine learning. Previously, he was Vice President of Marketing at Reltio.

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