Tuesday, February 23, 2010

Sentiment Analytics: Next Wave in BI

Business spends huge sums shaping brand image and promoting brand awareness. To gauge the effectiveness of particular campaigns, brand managers will study transactions, for instance sales made in response to direct mail or using coupons, web-page visits and ad click-through, etc. But study of past transactions is of limited use in understanding potential buyers who are not responding to market messaging, in understanding competitive positioning and in picking up on nascent trends. Surveys and social-media mining, especially for attitudinal indicators, can fill the gap.

Recently, I was talking to the marketing executive of a software firm. He said "We are spending huge amount of money and efforts to promote brand awareness. But we can't measure effiectiveness of the same. We have to heavily rely on surveys. By the time we receive survey results, it's too late to take any corrective action." I am sure there are lot of companies in the market who have similar pain.

There are several tools available in market today which can help you measure sentiment of people about your services, product & brand.What do customers, reviewers, the business community – thought leaders and the public – think about your company and your company's products and services – and about your competitors? What can you learn that will help you improve design and quality, positioning, and messaging and also respond quickly to complaints?

Recently, we did a PoV for a bank in India. We have found out that people are not very happy with their branch banking services. Things that they didn't like about bank were long queues & inadequet parking space around bank's branch. When we further drilled down to investigate, we found out that long queues were primarily due to very high number of customers in that area compared to number of branches. The bank took corrective action immediately. They have shifted branch to a location where in there is ample parking space, and opened one more branch.

One of the company is using sentiment analytics to determine which executives have the highest correlation to positively moving the stock price when they deliver positive news. They found that certain executives had a positive influence on the markets, while others actually had a negative influence because of the tone of their delivery. This is very interesting. Stock market is often driven by sentiments of people. I have noticed one thing since Obama took over as president of America. Whenever Obama delivers a public speech, there is a negative sentiment and decline in indian stock exchange index(SENSEX).

One of the bank is using sentiment analytics to determine whether their customers are happy with their services and products or not. If a customer is happy with bank's service then they are passing that lead to marketing dept so that they can cross sell/up sell more products.

One of the consumer electronics company is using sentiment manager to analyze feedback about their newly launched product on review sites such as Amazon & CNET. They use this feedback as input to their product development lifecycle.

There are several such examples of sentiment analytics. I think this is going to be next wave in business intelligence space.Sentiment analytics can help customers to make more sense out of their Business Intelligence reports and KPIs. If your sales is going down in one region then is it because
1. Your sales team is not efficient or
2. Your supply chain is weak which results into frequent stock outs at dealer place/store or
3. Your brand is percieved as expensive or low quality goods or bad customer service.

Monday, February 1, 2010

Successful BI Strategy - Part II

A BI initiative is of no use if it is not driven by the objectives of the enterprise. Implementing a BI solution should help an enterprise achieve the objective of advancing business by making the best use of information.

Dos and Don'ts for successful BI/DWH project implementation:

Do not start with a big bang implementation approach. Iterative implementation approach works well with BI project. Identify a business objective and deliver it via BI/DWH within first two-three months. Longer you take to deliver your first output from BI/DWH, higher is the possibility of failure. It is very important to deliver first output from BI/DWH on time with good quality. This will also help in selling BI/DWH vision to business teams. The shorter implementation cycles would be quite beneficial for the end users as well in terms of cost and time as they would have a much better feel of the end product, they would be able to modify the scope based on what is implemented after each cycle.

Do not try to roll out BI/DWH to many departments/groups at a time in first phase. If possible choose either Sales or Finance department for first phase as these areas are more closer to heart of CEO/CFO of the organization. It is easier to gain acceptability of an initiative if it has C-level executives acceptability & support.

Do not over burden end users with lot of trainings initially. If end users have to go through multiple days of trainings to use new BI/DWH system then there is a high probability that they will not use the system. Always look at maturity of a user group before delivering reports to them. If a user group has been using excel based static reports for past few years then give them reports which has drill down and parameter selection criteria. If someone has been using parameters based reports then give them OLAP based reports which will allow them to slice & dice the data on the fly. If someone has been using OLAP based reports then give them access to adhoc reporting tool.These will help in reducing training efforts that are required to use new BI/DWH system.Also, it makes transition to the new system easier and smooth. Lot of time static report users are given access to OLAP cubes which requires huge training efforts and time.Also, it requires steep learning curve, and it often demotivates them from using new BI/DWH system. Do not drastically change the way they are consuming information now. The change has to be gradual.