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This is the latest in BIA/Kelsey’s Vantage Points series. On a semi-weekly basis, it will tap the perspectives of various lookout points from around the local media and tech sectors. The views expressed do not necessarily reflect that of BIA/Kelsey. Please contact mbolandATbiakelsey if you have insights to share. 

The Current State of Demand Generation

By Mo Yehia

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SMB technology has never been hotter. As SMBs digitize, the tech vendors catering to them grows rapidly. A dozen SMB tech vendors have gone public in the last year, and some 40K have likely been started. Whoa, Nelly, it’s getting Hot in Herre.

With so many vendors vying for small businesses’ business, what once was a land grab is now a feeding frenzy worthy of Shark Week: millions of SMB prospects and hundreds of thousands of salespeople and marketers from thousands of vendors (and growing) vying for them, and no end in sight to the perpetual chaos.

In fact, on the average day, it’s not uncommon for business owners to receive more calls from vendors than from actual customers. SMB tech vendors need effective ways to source leads. Smart demand generation is one way to stop the current madness and allow vendors to focus their efforts on prospective studs while avoiding inevitable duds.

I previously wrote about data-driven insights, but now turn my attention to the current state of demand generation. Here’s the good, the bad, and the ugly.

Data Licensing

  • Example Peers: Hoovers, Infogroup, Localeze
  • Category Pitch: Incumbent data juggernauts powering Points of Interest for search engines, directories, etc.
  • Example Use: Google Maps wants to supplement POIs with third-party business data
  • Category Pros: Vast/global business coverage (up to 100s of millions of businesses), low cost, not limited to businesses with an online presence
  • Category Cons: Focus on traditional variables (e.g. revenue, # of employees, address), light on analytics (i.e. near exclusive focus on data), low depth of variables, large minimum order

Marketing Intelligence

  • Example PeersBuzzBoard, Radius, Sidewalk (my startup)
  • Category Pitch: New-age business intelligence solutions aimed at salespeople and marketers
  • Example Use: Groupon wants to arm its salespeople with information on popular, tech-savvy, quick service restaurants in the top 50 major metros
  • Category Pros: Focus on digital variables (e.g. listings, reviews, advertising), heavy on analytics (e.g. prospect scoring, predictive modeling), high depth of variables, heavy on (V)SMB coverage
  • Category Cons: Narrow/non-global business coverage (up to 10s of millions of businesses), limited to businesses with an online presence, (some) made for enterprise customers (e.g. newspapers, Fortune 500)

Automated Sales

  • Example PeersCrushpath, Growbots, HipLead, MerchantAtlas
  • Category Pitch: Automated customer acquisition to replace/complement salespeople
  • Example Use: Olark wants to find mid-size eComm sites receptive to adding a live chat solution
  • Category Pros: Highly scalable, more economical than a salesperson, lead generation + digital outreach
  • Category Cons: Black-box “algorithm,” large minimum order, not self-serve

Crowdsourced Data 

  • Example PeersLeadGenius, Mechanical Turk, ProspectWise, Upwork
  • Category Pitch: Human-vetted/crowdsourced solutions for tough to collect data
  • Example Use: Lightspeed POS wants to find small brick & mortar retailers that don’t have an existing POS
  • Category Pros: High accuracy (theoretically), tough to find data (e.g. POS system), highly customizable variables
  • Category Cons: Slow turnaround time, challenges with scale (e.g. managing dozens of freelancers), (some) not self-serve

Predictive Analytics 

  • Example PeersFlipTop, Infer, SalesPredict
  • Category Pitch: Predictive analytics solutions to increase conversions and velocity but decrease churn
  • Example Use: Desk.com wants to score leads so reps can focus on the segments that are most likely to convert and least likely to churn
  • Category Pros: Made for enterprise customers (i.e. BigCo not startup), transaction-level focus
  • Category Cons: Light on (V)SMB coverage, black-box “algorithm,” large minimum order, (some) not self-serve

Contact Management

  • Example PeersClearbit, Data.com, FullContact
  • Category Pitch: Contact information focused solutions that find, manage, and maintain contacts
  • Example Use: ConceptDrop wants to find contact information for CMOs of large pharma companies for sales pitches
  • Category Pros: (Some) heavy on SME/large enterprise coverage (e.g. info on Fortune 500 CMO not SMB owner/operator), low cost, self-serve, developer friendly
  • Category Cons: Light on (V)SMB coverage, near exclusive focus on contact information

Online Prospecting

  • Example PeersBuiltWith, Datanyze, HG Data
  • Category Pitch: Web technology tracking focused on identifying widgets, analytics, frameworks, content management systems, etc
  • Example Use: ReTargeter wants to identify websites that use their competitor, AdRoll
  • Category Pros: Online marketer focus, self-serve, made for enterprise (tech) customers
  • Category Cons: Light on (V)SMB coverage, focus on web technologies, limited to businesses with an online presence, excludes contact information

Points of Interest Databases

  • Example PeersChain Store Guide, CHD Expert, Factual
  • Category Pitch: Specialty databases for places/Points of Interest
  • Example Use: OpenTable wants to bolster its restaurant database with extended attributes like cuisine type
  • Category Pros: Low cost (as low as a few cents per record), high depth of variables (e.g. 43 restaurant-specific attributes), developer friendly, heavy on (V)SMB coverage
  • Category Cons: Focus on traditional variables (e.g. revenue, # of employees, address), light on analytics

Of course the biggest category I omitted is the status quo — most often synonymous with  manual prospecting. By some estimates, salespeople spend up to 80 percent of their time on lead qualification and cold calling, not selling.

Anecdotally, when I reach out to salespeople or marketers and ask how they find qualified prospects today, I overwhelmingly hear “I didn’t know this existed” and “the best reps (manually) do this themselves via Googling, drive-bys, meetups, etc.” Occasionally I hear “We tried to roll/rolled our own internal solution,” but seldom do I hear “We use an external demand generation solution.” I guess old habits die hard.

My goal here is to present some quick & dirty alternatives for technology vendors looking to make sense of demand generation alternatives. As a disclaimer, I didn’t consult with individual companies (1), and some of the companies above may crossover into multiple categories (2). The Peers listed are merely representative, not remotely definitive (3), and sometimes maintaining the status quo works phenomenally (4). That said, if you’re not using demand generation, you’re almost certainly not operating at maximum efficiency.

What I’m trying to say is:

SMB sales is really a bore, but those who successfully navigate it are worthy of folklore.

Stop listening to sales reps & marketers Yelp (pun intended), let data-driven insights help.


AAEAAQAAAAAAAALtAAAAJGQzMjNkNTNiLWY1ZjEtNDUzZC04OTE0LTIwMjc2ZjdkYTM4NAMo Yehia is a former banker turned human and co-founder of Sidewalk. He’s lesser known for stints at Sparkle Buggy Car Wash and Lehman Brothers. Backed by 500 Startups, Sidewalk’s business intelligence helps sales and marketing teams close more deals faster and to their dream SMB clients. Sidewalk scores SMBs from 0-100 to determine their social rank and receptivity to your product (so you don’t have to).    

 

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(1) I used my best interpretation of the landscape based on my knowledge and research. I welcome any and all feedback and apologize in advance for any mis-categorizations; there’s a subjective component to this.

(2) Radius sells to Fortune 500 companies but also SMB technology vendors; Factual sells a developer centric POI API but also a contextual ad-targeting solutions to brands; Sidewalk is bionic, employing manual reviewers to supplement automated data aggregation; FullContact and Clearbit also have company APIs; and companies are horizontally integrating left and right (e.g. DNB bought FlipTop), etc.

(3) I’ve made no attempt to thoroughly profile the 1000+ company strong and growing marketing technology landscape available to salespeople and marketers.

(4) Just ask Pere Rigo, a friend and founder of Package Zen. He’s built what I believe to be one of the most sophisticated demand generation engines I’ve seen. Companies like Groupon, GoDaddy, and Intuit, with a combined manpower greater than that of the Kenyan army (literally), have also invested heavily in internal demand generation tools.

This Post Has 5 Comments

  1. Hey, thanks for mentioning Growbots!
    Automated sales is about complementing salespeople rather than replacing them. The whole idea circles around the fact that parts of the sales pipeline could be automated to save salespeople’s time. That way they could spend it on the parts that bring the biggest value to the process: talking to and winning customers. That’s why not only the lead generation but also digital outreach should be automated, because those two activities are the most time consuming.

  2. Thank for the article! As for research tools, BuiltWith seems to be a little bit outdated. Allora.io and Datanize both provide much cleaner data but Allora is twice cheaper 🙂

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