Commercial Qualitative Market Research

It is difficult when you are handed down a paradigm and asked to fit in – especially so when you think that your data does not fit the paradigm. This can happen when you are working with an intelligent client who also dabbles in quick and ready research. Paradigms never fit neatly into qualitative data – especially when your paradigm comes from outside the research and you want to fit in your findings to relationships between broad constructs that come from elsewhere – prior work, ubiquitous commonsense etc.

This is where I would turn against myself and ask about for micro-research – unified fields are good for the synthetic imagination but what if they do not exist? At the micro level – what if the data fit into smaller chunks (many factors) – unless you are able to replicate the research many times or follow up on certain hypotheses, it does look improbable that you will be able to tie these factors together. But if the number of such factors is not so large as to become unwieldy, overarching theories may not be necessary and a peace-meal digestion may work  better by ensuring that the details are not lost in overarching theory. In practical business problems, this may be of great help until new facts pour in. But most of us will not be able to resist the tendency to come up more intelligent than we are – grandiose is a virtue we Indians adore. But to hell with the facts?

Look at it this way – most grandiose theories are but commonsense made more presentable – unless they contradict something that we would have considered intuitive and have data backing this contrary finding. If I can give you 5 action points to push sales of your skin care product in Salem, does it matter to you whether I present them to you neatly packaged under people, processes, strategy, promotions etc. (worse still, under the 4Ps one gets to see in business analytics presentations) and then bring in some folk wisdom to hold them together? There is nothing wrong with the packaging –in fact, these packages serve as useful mnemonic guides. The trouble starts when you start brining in your pet theories (or your manager’s) to tie together different parts of the package.

I am tempted to believe that most research remains in the boardrooms – they are discussed, presented, clapped for (now, you need real hot looking theory building for that) but rarely acted on. This is mostly true for small and medium companies. But theories can be important when you need to reinterpret findings to fit your pre-decided action plan. Then you say – look data says this (it doesn’t – there’s no data, there is theory) and I am all for scientific management!

The above sounds pathetically phobic. However, I am beginning to believe that qualitative data is a serious threat to sound management practice until we learn to do the following:

·         Build theory only the basis of prior work where substantial prior work exists

·         Where prior work does not exist, test your hypothesis – follow-up with more research

o   More intensive and focused research around a few key unanswered questions

o   A larger research piece with more cases (larger sample) and more stringent hypothesis acceptance criteria

·         Post-code and go only as far as a numerical frequency analysis of codes if none of the above are possible. Linking codes into a theoretical network is risky unless

o   There are clear co-occurrence patterns

o    There is earlier empirical work validating your links

In most real life commercial problems, one is working under short timelines, prior work in the specific project area is rare to come by, the research is very context specific and one does not have the luxury of a full-fledged research program. Clippings from industry publications and the  general business press can, however, feed into your research armory (its convenient to have web-clipping tools here rather than rely on manual copy-paste – try Evernote). This can be bolstered by interviews with select industry experts, trackers. It is best to run your code networks through a couple of industry experts – look for dissonances and rely on a quick Delphi to generate your final network of codes. BTW, I love Atlas.ti and its features for creating codes, meta-codes and code networks.

Build all this beforehand into your research proposal – anticipate areas where you might need to fill in the blanks. If you proceed with care, you can still come up with something useful for managerial decision making. Also, at the end of the day, you would have a good night's sleep!