I believe that online businesses have a key edge over offline businesses – they are able to easily gather data on customers, the purchase funnel and conduct iterative A/B testing. Harnessing this data and using it to drive decisions for customer acquisition, product development and generally having excellent management information (MI) is critical to executing a successful internet business.
There are three things that I want to touch on in this post:
Using Metrics to raise financing: While I was working in VC last summer, I encountered many entrepreneurs and it was interesting to see how they all thought about and ran their businesses. It was significantly more impressive and informative when the entrepreneurs understood the right metrics for their business. It allowed them to educate us on the important variables and what the implications were for their business and it also made it easier to compare the business against other models that we were familiar with. I think that it shows professionalism and credibility to be on top of this information and it was definitely something we used to screen entrepreneurs.
Segmenting customer base – yield optimal unit economics: Once the product has been launched and the customer base starts to expand I think it’s really important to start to segment the customer base and understand the motivations and unit economics of each segment. I think you should start by understanding what attributes that you can use to segment customers – demographic information, source of click, etc and then measure these attributes against engagement metrics, revenue per user, social metrics etc. This will allow you to identify different user groups, understand what motivates them (potentially through qualitative studies) and plot their evolution over time. This data would be extremely useful to drive product changes as well as acquire specific types of customers.
For example: I was recently talking to Pasha Sadri at Polyvore (a social fashion site where people create sets or outfits which are shared with the community) and a handful of talented “creators” drive 80% of the traffic to the site (approx. 6M monthly users). If they were able to identify patterns about where these creators come from / demographic it would be easier to acquire more creators and they would drive significantly more traffic to the site.
Product changes – A/B testing: This is a pretty heavily blogged about topic but I think you should use data and metrics to drive and measure incremental product changes. It’s especially efficient when you have a suite of products with similar features and you can leverage learnings from one product change and apply it to the family of products. Zynga are especially good at A/B testing and they have learnt best practice in monetisation/virality and roll out their learnings to new and existing social games very effectively.