“Analytics as service” for SMBs – Part 2

Some SMBs utilize services of analyst today. The analyst helps SMB owner to make decisions today to decide businesses approaches to help business to generate more revenue.    Though there are analytical approaches to reduce cost and manage inventory and arrive at right prices, my idea of the blog  is around customer acquisition which is critical for the business.

Most of the the business owner would answer “Yes” to both the below questions. They would also be ready to pay if they see a logical route to achieve the below two goals.

  • Do you want more customers?
  • Do you want more money from existing customers?

Increase in number of customers and increase the money generated from every customer means growth in revenue, business. Let us consider a scenario that happens today where analyst is engaged to help small business today.

The marketing/sales manager of SMB proposes to the SMB owner with a proposal to run a specific marketing campaign or open a new store in a particular area.   Where the campaign proposal is similar to previous times, SMB owner finds it easier and simpler to approve the proposal with awareness that the last year campaign provided a comfortable result and he assumes the same would happen this year also.

The marketing and sales managers provide cost estimates for approval to be spend to reach the projected milestone. If there is new innovative business proposal where SMB owner has less awareness, SMB owner is aware of the decision on which both future business revenue and the cost to be spend to earn revenue depends. To mitigate the risk to take decision, SMB owner engages with a trusted analyst, known for a long time to help with the  decision.

The trusted analyst neither works for SMB and neither has access to customer data of the SMBs.  The analyst needs to bet on his experience and intuition and market relationship to recommend to go forward with  the business actions for the SMB owner. To be true to his profession, the analyst asks SMB owner for the data about customer and requests for reports. SMB owner connects with IT person in organization to check whether he can pull and present the data.

IT person requests for sufficient  time to provide necessary reports. Let us accept that IT person might have no understanding of the database structure and there is process to connect with IT expert to get the required data in desired format. IT person asks analyst  to specify what is the data needed. When the analyst asks what is the data available, the IT person has limited knowledge about data beyond standard reports.

SMB owner observes that business analyst requested for data and his organization is not able to provide data.  He also observes that business analyst had recommended a decision based on his experience and insights from his business network.

The suggestion of the business analyst seems to match with the intuition in SMB owner’s mind. SMB owner is not clear whether he had casually shared the intuition to the analyst  and analyst is projecting the same as insights.  As there is trust and long term association, the recommendation of the analyst are approved based on faith and personal touch.

Today when there is no analytics,  there are no elaborate mechanism to capture the recommendation of the analyst and also the outcome of the campaign or decision based on the proposal. Effectively there is no measure captured for future reference. The analyst is handicapped at the end of the time period to verify whether the recommendation resulted in to favourable  results for the business.

Analytics’s in place helps to implement  “Propose- Measure -Learn” feedback cycle . Here the recommendations are captured and the approach to measure the actual result is planned  before implementing the recommendation.  At the end of the analytics cycle, the  analyst can understand the gap between projection and captured actual result.

This enables the analyst to identify the reason behind the gap and also validate the extent of the actual measured results against the recommendations. The  insight from measurement against projection helps the analyst to modify or tinker recommendation for the next  business time interval.

With analytics in place, “Analytics as service” provider can evaluate how to capture the following value add customer  information  to get better insights.

  • How to integrate customer social networking data to get better insights?
  • How to make use of external available industry insights about customer from the same domain space?