Prospecting hell: Why B2B search tools have to die

Why B2B search tools have to die

There are tons of lead building lists out there, claiming more contacts, more companies, more depth to qualify your leads. All providers advertise on the size, coverage and quality of their database. To write on this topic, I’ve tested a dozen of « lead generation » services. The ultimate frontier (as it seems) is to provide the user with multiple and complex search criteria. Thus users easily spend 10 minutes to understand the search filters. And this is called the « state of the art » !

I don’t want to blame others: IKO System has also implemented « advanced search » features as our users keep asking for more criteria to better target and build their list of prospects. Even if we differentiate ourselves by working on social data, I don’t feel confortable with this service: if we address search Ninjas with complex requests we probably lose occasional users…

And there are many other collateral damages :

Duplicates : Users search, filter and save requests (as agents) with multiple search criteria. Therefore lots of agents cannibalize each other, generating duplicates.

Lost control : When you’ve created twenty or so lists and agents, you lose control on what you cover and what you don’t.

Managing lists: Old searches and agents still run and retrieve new leads while you probably do not keep looking at this prospecting field. Two times a year, you have to clean up the mess and modify/suppress your old agents. This can be a real burden.

Quantity over quality : While finding leads and buying lists is now easy and cheap, the top issue in prospecting is to qualify leads, focus on the best and most promising ones, and be able to trash leads (which is not easy).

Make an educated guess

Everyone wants control but no one wants to play the chimp with long unqualified lists and complex criteria. Are the market players able to provide better tools ? Look at Google search : results are not only based on your search terms, but also on your profile. Google qualifies what you like/read/search and changes results upside down to personalize the search experience. In plain English, Google engineers consider they know what you look for better that you know it yourself. I have the feeling they are right : the data overwhelming issue leads to personalized algorithms.

Now reconsider the topic of building lists of leads for prospecting. If we tap into the sales rep CRM data, its professional networks and the contacts and accounts he works on, we have enough data to set a neat profile of what the sales rep looks for. Probably better than he does himself.

This is the idea we started implementing in the « Magic leads » feature. The user profile is calculated on his prospect/client accounts (size, industry, location) and decision makers he addresses (seniority, job function, title). The profile is computed every 24h and leads are generated on these criteria.

It is still not perfect but it’s a start. We probably need to dig into contacts’ resumes, tune the user prospecting territories, run semantic analyses on company websites, discussion groups, etc… This leads to years of exciting R&D ahead !

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