When I began my career as a Market Research Analyst and Marketer, I had the opportunity to participate in all of the stages of a conventional market research project. Besides being a very interesting experience, it allowed me to understand the whole process behind the report that I usually received and used to make decisions.

From the planning stage of the research project, the field work (when individuals go house-to-house surveying the public) and tabulation of data through to cross-checking and analysis of data and the final report, there is an infinite number of difficult steps involved that constantly place the quality of the information at risk. It was only after participating in the whole process that I was able to understand the difficulty and the amount of work behind the reports that I received and which after spending only a few hours reading, enabled me to make a decision that could multiply the profits of a company.

In a few words, this is what Google developed—an incredibly intelligent platform capable of providing us relevant content from millions (or hundreds of millions) of documents on the web. Behind Google is an extremely complex system of algorithms and information systems that no doubt bare more resemblance to a science fiction film than to a tool used by even the most inexperienced of Internet users. This is because the complexity lies behind the screen while on the front of the screen there is only an empty text field and a search button (okay, two search buttons…).

A few years after Google came out, when we began to think about something which today is called Socialmetrix Echo, we had the same idea—generate a tool that from an extremely simple interface makes it possible to make extremely valuable decisions.

But what is behind Socialmetrix Echo? Everything begins with a tool that navigates the Internet and brings a Web page’s code to our databases. We must take into account the fact that for a computer, that which we call a word, text and to an even greater extent  language, does not exist.

So, moving onwards to the next page.

This is what our databases receive (in reality this is only part of what they receive… there’s a lot more code involved).

As you see, there is no such thing as the text of a post, or the text of a comment, or the date of a post or the name of an author. There is only a strange group of incomprehensible text.

The step prior to this one involves Socialmetrix Echo understanding where to find a text, date, author etc., and saving each in a different location in the database.

Afterwards, the text field is processed by a language-processing algorithm. What does this mean? The majority of tools that analyze, “what people are saying on the Internet” search for co-occurrences in words. A very simple example is if in the same text appears [Juan Damia] next to [excellent post] these tools “understand” that Juan Damia (that is, me) received a positive comment. However, the text could have been, “Juan Damia had better write an excellent post or take up another field of work.” That is, if we can’t understand what the tool is “understanding” (even with a margin of error), we won’t be able to use that information to make decisions. That’s because basically we don’t know how secure the context upon which we are basing the decisions is. Furthermore, this type of tool does not know what a brand or product is, and even less so a characteristic of a product. Since words are only a group of letters, if there is a concurrence between those words, the tools interpret A as being equal to B and count, for example, “a mention”, and nothing more.

Socialmetrix Echo processes language and bases the aforementioned process in an information framework for industry that makes it possible to understand when people are talking about a product, a brand or a characteristic. It identifies the importance of each word within a particular context because it is based on “grammatical structures” and learns from human beings. Of course, when we say “learn”, it means that it generates statistical processes in order to be able to understand the sentiment behind a text (or that which humans refer to as text).

When we access Socialmetrix Echo, it is apparent that it is a clean and clear interface. Each report responds to questions from different functional positions within a company. When we see the characteristics of a report, in just 5 seconds we know which of our product’s and/or competitor’s characteristics people like, and which they don’t. In 10 minutes we can do an FODA analysis and in the next 2 minutes send a report to the Product Manager so that he or she can “balance” the product so that it coincides with user preferences.

In the same way, in only a few more hours, it’s possible to see how a television campaign that we launched was received and if it’s achieving the desired communication effects. It has occurred to me that in much the same way, the writer of a soap opera could follow-up on what people think of a program and then modify or rewrite the story based on that information.

This information makes it possible for us to generate contexts and to make decisions in a much more secure manner and at a speed previously almost unthinkable with other types of research.

Does this mean that Socialmetrix Echo functions as a substitute for conventional market research? Clearly it does not. But it means that we can access information much more quickly and that the information will be without bias and generated when someone wants to comment and not when they are asked to do so. Afterwards, based on this information, it is possible to identify what further research should be done by the Market Research department in order to better understand the “reality”.

Thus, Socialmetrix Echo is not a substitute but a complement to traditional Market Research. It is a new tool which generates relevant information that enables decision-making.

Often times when I present the tool, I’m told, “But this is possible with other types of free tools.” This amuses me since Socialmetrix Echo was created because I personally had to deal with difficulties in obtaining information through other means. I found that I faced the following problems:

1-Google Trends (or Insights for search): This is a tool that detects what people search for on the Internet and not what they say.

2-Google Search: Detects the number of documents (and not mentions) in its database, many of which are not relevant and are difficult to disambiguate (Pancho could mean a sausage in Argentina or a national hero in Mexico, to give a silly example). We also can’t select specific dates since the only options are “last month”, “last three months”, “last year” or the entire database (for which we have no time reference). We also can’t tell if the results are content that’s been generated by users or content from a brand’s corporate page, for example. Nor can we tell if these results are for a particular day, which makes it difficult to understand what happened after for example, a marketing campaign.

Finally, it’s logical that we also can’t find out what’s being said, that is, if what’s being said about one of our brands, products or characteristics or those of the competition is positive or negative.

3-Google BlogSearch: With the exception of the option to select a specific date, this tool has the same problems as it’s brother Google Search.

The rest of the sources, to a greater or lesser extent, have the same problems. This means that it is not only impossible to obtain similar information in an acceptable period of time, but that the information obtained by search engines is not able to report the state, flow and sentiment of the buzz on the Internet. In addition, Google Insights searchers are a complementary source to Socialmetrix Echo and the two work excellently together. The fact that people search for something and that they talk about something are obviously two different things and for this reason when used together Socialmetrix Echo and Google Insights provide complementary information.

Each tool was developed for a very clear purpose. The purpose of Google Search is to return the most relevant results for a search. Google Blogsearch has the same purpose but with information from Blogs. Google Insights for Search’s purpose is to report what people search for. Socialmetrix Echo was developed for the purpose of reporting what and how people say what they do about its different Brands, Products and Product Characteristics and those of the its competitors.

Enhance the decision-making process with Socialmetrix Echo!