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Traditionally when data sources were limited, there were different kinds of processes in place at the market research firms. Reports were created out of manually entering data into systems and results were later visualized via some standard analyses. But with the exponential rise in data volume, both online and offline (because of online resources), techniques have changed over the period. Simply said, gathering and managing that humongous data is like running another market research firm, forget deriving analyses from it.

Given that, how do we think are the market research firms managing to stay ahead of the curve and away from the noise in such a data-intensive environment? Before that, lets try to get a view of why this data is even required in the first place.

1. Brand monitoring companies feed on data. The more data they have, the larger is their sample to draw out conclusions from regarding brands at certain points in time. Data is collected from all forums possible that discuss any brand they would like to track, for a given set of keywords. For example, we’ve had a brand monitoring client only looking to listen to people talk about the sport equipment manufacturers, for the keywords “good” , “bad” and “terrible”. Such conclusions are then released to the public (or the manufacturer as may be the case) to decide and react- quite similar to the stock market scenario.

Data as a serviceBrand monitoring via social listening
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2. Sentiment Analysis is probably that parent of market research that it idolizes on. The vogue is to
track everything positive/negative/neutral being said about anything on earth and social media is the usual resort.

Brand Monitoring
3. Analyzing market trends is another usual suspect. Time and again, it declares trends like- if the industries are running towards big data for real benefits or if its pure hype, or if Samsung is winning the smartphone race or iPhone is already the winner. This again involves collating facts and figures from various sources and expert polls. Such analyses are quite interesting and informative for the media or for those who are not IN yet.
Now that we realize how much is being done with the data around us, its important to understand what goes in the background to generate these analyses. Most of these firms outsource the data collection task to Data as a Service (DaaS) providers who have a flair for extracting data from the deep web in near real-time. Others try their hands on it themselves by employing a data team, but sooner or later switch back to the former model. Lets dig into the realities of using such a model to support your company’s research.


1. Data coverage

This is extremely important given the competition around but fairly difficult due to the dynamism in content. DaaS providers have technologies in place and learnings that come from previous experiences, so they have already crossed this barrier. To ensure that nothing was amiss, some research firms have multiple data vendors. When you do it yourself, catching up with changing data is resource-intensive.

2. They already do it for others

Since they have already built a platform that caters to many other similar companies, most of the efforts get balanced out. So why re-invent the wheel when such a solution is more cost-effective and much less painful.

Waiting queue Do it yourself vs. give me the best!
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3. Channelizing other functionalities

Since the DaaS providers already deal with various technologies, they might as well add few other components to it in order to deliver cleaner data. Essentially, techniques like data de-duplication, near duplicate detection and named entity recognition are performed on the crawled data and provided in an extremely usable format. This makes the researcher’s life simple.


1. Myth- Reliability is an issue with external vendors.
Reality- This issue is true with choosing any vendor for just any other work. Since most of the research rests on the data backbone, it can sometimes get intimidating to involve an external entity. But with so much data floating around these days, its much easier to arrive at peace by not doing it yourself.
2. Myth- I’ll get locked in with the vendor after making a choice and will be bound to use their services even if not satisfied.
Reality- Well, this is true for any other service that you pick which is why properly evaluating your vendor counts.
3. Myth- Costs are unusually high. Especially if rolling back from the vendor because I’d have lost the time, money invested and am back to square one. 
Reality- It’s actually the opposite. Most of the “as a service” companies are based on an ongoing cost model where you pay for as much as you use. And hence, if a research firm picks a vendor and stops using their service after a couple of months, its actually the vendor who’s in deep trouble given all the initial investments they’d have to put in.
4. Myth- You will give the same data to someone else.
Reality- This is a misplaced worry that tops everything discussed so far. All the data that gets delivered is public, and if another company doesn’t take it from us, they might as well take it from any other vendor. So it’s difficult to reserve the exclusive rights to data because even the DaaS providers don’t own it.

On a concluding note, we’ve seen most of the market research firms look towards DaaS providers these days due to all the reasons mentioned above- increasing data volumes, scalability issues, technology barriers and effort required. The results have been much appreciated in the market because of data qualities and ease of use of their platforms.

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