olivergajek

Early on in the life of a startup you sell to friends and family and you service incoming requests that may be generated via marketing and/or viral infection. Depending on the nature of your product and your market that may be all the lead generation and sales process you will ever need. Most of us, however, are not that lucky. We may be offering a radically new product to an existing market or we may be bold enough to create a completely new market. In the former case we may have some opportunity for online lead generation via SEO or SEM, but we may not have the budget necessary to compete in a noisy search environment. In the latter case SEO/SEM may very well have no relevance whatsoever to our lead generation efforts, as the market does not yet know about its existence and its related terminology.

So for most of us there comes a critical juncture where we need to ramp up revenues by reaching out to prospects and by starting a conversation with a large number of prospects, which will educate the market in general and will hopefully lead to buyer interest and ultimately to signed contracts and revenue. In the early days this process will be managed by one or more of the founders, typically with limited process and tools. Things get more complex, however, as marketing and sales resources are brought on board and as the organization needs to start managing and scaling a process that was previously executed in a more intuitive fashion. Keeping in mind that many companies are started by technical founders with limited sales and marketing experience it becomes obvious that there is a steep learning curve. I will cover many relevant issues in future posts.

For obvious reasons I will start with an overview of the fundamental mechanics for Lead Management. This is an issue even if you have no systematic effort for Lead Generation in place. Incoming online requests and business cards collected during a trade show are already a lead pool that needs to be managed.

Some good observations on TechCrunch by Vinod Khosla recently (here and here) on a potential renaissance of Artificial Intelligence in the upcoming years:

 “Location, social networks, identity, and personalization are just the tip of the iceberg. There will be countless new types of data streams and new ways to make data useful. Fundamental data utilities and applications will be built on these and a lot more information and data reduction will be extracted from this hairy-looking big ball of often-unstructured data.”

This could play out in three dimensions:

• Natural interaction (voice, text, gesture) that finally is beginning to work as computing power has come down so drastically that many of the mainly statistics-based approaches can actually work and scale, producing meaningful results.
• A new metaphor for interacting with information and services based on an intelligent assistant, popularized primarily by Apple’s Siri.
• The availability of large data sets (primarily the explicit and, more importantly, implicit online behavior of hundreds of millions of users) feeding meaningful and non-trivial pattern recognition approaches that discover meaning in very large amounts of data.

Some caveats apply:

• It is unclear how far the intelligent assistant metaphor will scale. Anthropomorphizing the machine is useful because it drives end-user habit formation, but can quickly backfire where naive and unrealistic expectations cannot be met.
• If innovation is driven by collecting more data about more people then the open issue of how to deal effectively and on a global scale with issues of online privacy will rear its ugly head. In one potential scenario we may see more innovation and more customer value available to users in jurisdictions with less than stringent privacy rules and regulations. And vice versa.

Reading “The Startup of You” by LinkedIn founder Reid Hoffman and Ben Casnocha. Two valuable take aways on social graph design and potential:

• “Weak ties and acquaintances” can be very powerful, but are pretty difficult to keep alive and active in the real world. Social networks make it much easier or, in some cases, even automatic, to touch this outer circles of connections regularly and appropriately.
• “Three degrees of separation” enable a trust relationship with strangers, because there is an instance in the middle that is known to both strangers. Higher degrees of separation break down because there is no authentic basis for trust anymore.