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Relationship Data

A recent article in Inside CMX by Ted Rubin urged brands to concentrate on what he calls “Relationship Data.” In a world where “Big Data” is gaining ground, Rubin encouraged brands to not forget about the conversations and personal impact their companies have on people. 

“Relationship Data” begins to approach a problem that has gone unsolved for many years. Each relationship between two people is entirely unique and nearly unquantifiable. You can subjectively qualify your relationship with someone, but it may take awhile because relationships have so many nuances, especially depending on how much you know about that person or how long you’ve known him or her. Your relationship with that person may be nearly the same as the one another person has with him or her, but only on the surface. Change a single variable in that relationship (say, the sex of that other person), and you have a completely new set of dynamics and rules under which that relationship operates. Sociologists and research companies have been trying to quantify relationships for a long time, but creating a simple, standard ruler on which to measure all relationships is incredibly difficult.

This has business and operational implications as well. While a person or a small business may be able to qualify its relationship with customers between family employees and small teams, a larger organization has a much more difficult time communicating internally the relationship data it has with individuals in its audience. Also, many larger businesses have multiple operators or community managers for one social account. So while a consumer perceives the relationship with the brand as one entity through one account, that account is actually run by 3 or 4 people. Each of those people may not be familiar or understand the full capacity of the relationship that person perceives to have with the brand.

Take for instance this recent epic conversation between a consumer and multiple brands. Each of these brand accounts likely has more than one community manager. So, how are Tesco Mobile, Jaffa Cakes, Cadbury, and Yorkshire Tea going to describe their new relationships with each other and, more importantly, with Riccardo, the person? You may realize by now that tracking conversations for your relationship dataset may be a bigger bite than you can chew.

There are a few software solutions, such as EngageSciences, which capture all the historical conversations and interactions between consumer and brand. This would allow community managers to catch up on any missed relationship data while not on their shift. Secondly, EngageSciences also tracks the “health metric” engagements between individuals and your brand’s social media accounts. With that data, brands can make informed decisions when engaging in conversations with the individuals in their audiences. A workflow can be put in place that communicates those relationship data to anyone in the company.

Relationship data, while simple in concept, actually can be fairly complex. However, with a good tool to track it and combined with well-parsed “Big Data,” brands can empower themselves to make meaningful impacts on their consumers. More importantly, brands can engage with their consumers as individuals, as people.

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