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Research & Analytics – Build on Each Other

Over the last 10 years, Business Analytics has become a buzzword. Pioneered by companies like General Electric, Walmart, American Express, Netflix, Amazon, etc., it has today spread across industries and become the cornerstone of many companies. Companies are using analytics in making data driven business decisions to accelerate business impact.

The most talked about areas in Analytics today are Business Intelligence (BI), Big Data, Visualization, Data Mining, Predictive Modeling and Optimization. But another, equally important area in Analytics, ‘Research’ has seldom been spoken about much.

What is Research?

Research refers to the process of using structured and unstructured information from various sources – secondary, primary and social media to be able to come up with useful insights for business decisions. Data mining and advanced analytics focuses primarily on driving insights from internal transactional information of a business. But many parts and functions of the business does not necessarily have a lot of structured internal data and thereby arises the demand of data augmentation using Research.

Input Data – Primary Research comes in play, when there is need to collect data from primary sources like survey or focus groups. Financial Research relies on financial information of companies available in public sources, annual report etc. Business Research comes into play when the reliance if on unstructured data from internet, social media, publications, etc.

How companies use Research:

Research outputs are used in tracking new and existing markets, assessing competition and suppliers, comparing products and brands, validating benchmarks as well as researching customers.

Research – Moving from Information to Insights:

Information available on secondary sources can be used to generate newsletters/alerts regarding key markets, products, competitors or suppliers. At this stage, research is just nuggets of information. Its relevance is in its timing and its authenticity.

A variety of websites help one prepare such basic research outputs. The next step in the journey of research would be to actually use this mountain of information to provide alerts on future happenings.

For example, a “battle-card” for a new product launch is a research output, which would enable a Product Manager to compare the gaps in the features of the new product vis. comparable products. Or it could be an analysis of potential suppliers or companies which can be looked at for new growth opportunities.

The issues with Research today:

A lot of companies use Research today. But the use remains very fragmented and focuses only on one narrow area of research. Outsourcing and off-shoring of Research is also common.

Market Research agencies, Knowledge Process Outsourcing (KPO) units, niche research outfits and consulting firms all provide Research Services of different types. But the issues many of them face are as follows:

  • Lack of Domain knowledge – the teams are trained on Research tools and methods but often lack the market and domain knowledge to really understand the issues.
  • Data gathering vs. Research – Sometimes there is a dilution of some of the Research offerings. So in some cases, the front end teams work on the reports. The teams in the back-end offshore locations may not be even aware of the objective of the Research but are just asked to ‘search’ for relevant information.
  • Not harnessing the Power of Analytics – Though a lot of Companies possess both Research and Analytics teams, they rarely share knowledge and information to come up with a combined offerings. So Primary Data could be used to provide a report on Brand Perception or Customer Perception, Financial Results could be used to prepare a Quarterly Earnings Report and the News and Industry Trends could be used to generate a Market Assessment Report. While primary researchers use data mining sometimes, but there is, in general, room for making the analysis more insightful using advanced analytics techniques. It is rarely heard that a business researcher uses text mining to make his findings more objective.
  • Ability to provide Recommendations – The above 3 issues result in an inability to provide recommendations or actionable insights.

How Research can be used powerfully along with Analytics:

The real power of Research can be explored if one can use the data sources together and build in the Power of Analytics to actually provide recommendations or learnings for the future decisions.

Example of Using Research with Analytics:

Following shows one example where Research and Analytics can be used together to provide recommendations and insights –

Business Problem: Increase market share through new product launch.

Use of Business Research: Research current market share, competitor offerings, customer need, gaps in offerings and identify target segment.

Use of Survey Research: Analyse Customer Preferences and possible pricing through a Customer Survey / social media.

Use of Analytics: Estimate potential market size and pricing based on consumer preferences, previous product knowledge, and target customer segment.

Use of Financial Research: Prepare a make/buy decision based on Potential Market, Price Points etc. Arrive at Cost Benefit Analysis for Product Launch. Compare alternatives such as Make/Buy decision.

Final Output: Business plan for the New Product Launch.

In the above example, instead of just doing a survey for a new product launch or a tracking of market share, we are using all aspects of Research and Analytics to actually solve a business Problem.

What does the future hold in store?

Research can no longer be looked at separately from Analytics. With information availability no longer an issue, the need for Research to be relevant, timely and actionable will increasingly become more important.

The need to tap into real time information, e.g. social Media, will change the way traditional Research is conducted.

A lot of regular Research outputs like newsletters etc. will no longer be provided as Service but will be readily available as plug and play tools. Technology will play a great role in automating information and disseminating it very quickly.

So the differentiator for Research companies would be their power to combine information from various data sources and actually use Analytics to provide Recommendations.

Research will either become embedded in Technology or become embedded in Analytics and it would be up to Research Companies to decide whether would like to sell Research Tools or Recommendations.

As Einstein famously said ’Not everything that counts can be counted and not everything that be counted, counts’. It is time to make Research count, by adopting big data based analytical techniques to generate more sophisticated insights and using technology to make the insights more actionable for the business users.

The author is the CEO and co-founder of BRIDGEi2i Analytics Solutions. He can be contacted at

About BRIDGEi2i: BRIDGEi2i provides Business Analytics Solutions to enterprises globally, enabling them to achieve accelerated business impact harnessing the power of data. Our analytics services and technology solutions enable business managers to consume more meaningful information from big data, generate actionable insights from complex business problems and make data driven decisions across pan-enterprise processes to create sustainable business impact. To know more visit

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The views and opinions expressed in this article are those of the author and do not necessarily reflect the official position or viewpoint of BRIDGEi2i.