Last week I was looking at G2 Crowd, which is a crowdsourced technology review site, and it got me thinking about the future for tech analysts. Today the big analyst firms sell analysis that they’ve compiled through a variety of techniques and while there is no question that their experts add value, is that enough to warrant paying a premium? If a crowdsourcing site could gather reviews in sufficient volumes, authenticate reviewers, validate reviews (within reason), capture context, and apply analytics, then just maybe could it outperform the big analyst firms? Particularly as crowdsourcing becomes more broadly adopted and the type of analytics they do on the data becomes more sophisticated.
As the Internet becomes more integrated into all of our lives, driven in large part through mobile and social, we will all become increasingly interconnected. Our new interconnected world will contain multiple networks that represent different dimensions of people’s lives — social (Facebook), business (LinkedIn), food (Allrecipes), wine (Vivino), travel (TripAdvisor), movies (Netflix), fitness (Runtastic) — and cross the digital-physical divide (The Internet of Things).
Crowdsourcing sites like G2 Crowd will represent just one more type of network that will connect people with products and technology, telling you what products they used, what they thought of them, and what reviews they read, liked or shared. If you then link the crowdsourcing network to a business network like LinkedIn, you can connect companies to reviewers and bring with it lots of context that when comprehensively analyzed can transform your understanding of the reviews:
- Analyze the reviews for opinion. What companies are using what products, what they think of them, and why?
- Analyze the interactions for need and intent. If someone read lots of reviews about CRM systems, there is a reasonable chance they may need a CRM system. If they then share or recommend a particular review, that may indicate intent to buy or intent to investigate further. It may also indicate an attempt to sell, however this is easy to catch from the business network.
- Analyze the business network for context. Company name, maybe industry, products, location, social network (which itself could be analyzable for further context – what they are talking about, who they are associated with, etc.)
All this analysis lays down more data about the data, and allows you to model the products in a whole new way inferring new characteristics from the organizations providing the feedback. You can then provide analysis that is personalized around common attributes between organizations and provide a much deeper drill-down based on a broader set of harvested features.
This type of analysis goes way beyond what a traditional analyst can possibly achieve, although it clearly brings with it the risk of introducing noise. So, while I don’t believe the analyst is going anywhere anytime soon (and the great ones will always be in demand), I do believe that these new approaches to gathering and analyzing data will challenge the status quo. To what outcome, only time will tell.