Fusing qual and quant to understand how brands can connect with what’s happening thru Twitter

The horizon of human relations, including our deepest needs and interests, has extended to include the virtual space of the different social networks that have become the leading contact and communication platforms of our time. Social networks contain millions of conversations that simultaneously take place on these platforms.

However, despite the fact that each social network offers the potential for new contacts, brands do not always know how to take advantage of the opportunity to participate in people’s conversations with organic and relevant proposals. The lack of knowledge about the peculiarities of each of today’s major digital platforms (i.e. Twitter, Facebook and Instagram) has led companies to replicate their ATL campaigns in digital media, instead of leveraging the advantages implicit to understanding that each platform features differentiated interactions.

How to make a business breakthrough? Twitter Mexico, Arconte Research and Sinnia set out to answer the question by conducting a big data-qualitative research project to establish an actionable tool for clients and advertisers wishing to use Twitter as a contact platform with users, to maximise the real-time conversational properties that it provides.

The core purpose of our research was to build a bridge between people and their conversations with the world of brands. In other words, to identify the keys to generating brand content in real conversational situations. These efforts led us to organise a journey of interdisciplinary iterations, comprised of the following three steps:

Three steps to generate brand content

1. Detect: How do we organise the information in an insightful and actionable manner?

We know that Twitter is an almost infinite source of knowledge so the first stage was to set a specific period; we decided to understand the Trending Topics (TT) of 2017.

We started out by asking simple questions, such as how long does a TT last? Then we set out to work on Time-Series Clustering, and algorithm clustering. This provided us with a basic understanding of the behavior of the TT phenomenon, so it was time to ask some business questions:

• Are TTs predictable?
• Do TT need a hashtag?
• What are the most recurrent topics?
• Which topics last longer?

We identified the main variables requested by our partners to activate brand communications on Twitter:

• Predictability: can we know in advance that a TT such as #WorldCup will appear on a certain date? This makes live marketing much easier.
• Content classification: is this about sports, music, news, etc.?
• Personal vs. cultural calls-to-action: is this something about a personal point of view, or a cultural topic?

We then tagged each of the 5,834 trending topics to these three variables and analysed them with the information obtained earlier. The results were very interesting and showed us that:

• Around half of all TTs were totally predictable.
• About half of the TTs were sports-related and did not have a hashtag.
• The most recurrent TT in Mexico in 2017 was #HappyThursday.
• The TT that lasted the longest was #WeTheUgly.

We made an interesting, albeit obvious discovery, after looking at the most recurring TTs plus those that lasted more hours, which were also predictable. Predictable trending topics focus primarily on two topics

1. Lifecycles: #HappyMonday, #HappyTuesday and so on for the days of the week, but also #InTheMorning and #HaveAGoodWeekend, as moments of the day and of the week or month.
2. Passion Points:
   a. Sports: #CopaMx, ChampionsLeague and others.
   b. Music and radio: #ReclueMix, #JessieenExa, #SadShift and others.
   c. TV: #MasterChef, SharkTank and others.

What these hashtags had in common was that they empowered users to express their feelings about certain topics.

2. Understand: Converting clusters into conversational contexts

This work allowed us to answer the “what” of the conversations; however, we still needed to answer the “how” to take advantage of these conversations in the creative planning process. Therefore, the Arconte team set out to retrieve the cultural relevance for the most important hashtags.

We used deep interviews and close follow up with Twitter users so we could establish the references and relationships of the conversations detected in hashtags or mentions with the contextual, subjective and emotional realities driving them.

• Cultural environment: the offline framework or social context used to insert the hashtag that delimits a specific field of human relations. This is the big picture, without which we are not able to understand the conversation.

• Tension: we established the singular and profound truth that directly involves the user and his/her daily life with the hashtag. It can be presented as a need and the opportunity to satisfy it, such as the need to escape from daily negativity.

• Satisfaction: we identified the strategies that are used to address everyday life tensions or meet latent needs. This is where many hashtags offer an opportunity to integrate and become part of the solution.

3. Converse: Who has the right to participate in a hashtag?

We discovered that the starting point for a brand should invariably be the establishment of a relevant relationship with the conversational contexts. Therefore brands could participate in a conversation as long as they exploit a tangible and credible link that earns them the right to do so. This right can be obtained through the following three tangible points of the brand:

1. Product: my product or service is related directly to the subject matter. For example, #PersonalFinances – I offer financial products.
2. Positioning: my brand positioning is thematically the end of the topic. For example, #ChampionsLeague – I am Heineken, thus positioning is based on internationalisation.
3. Execution: my campaign execution, a tagline, is somehow related to the topic, such as #BeerDay with my advertising spot centered on bonding.

With this output we created an engagement kit that allowed brands to take advantage of the most predictable and frequent hashtags  —big data input— trough the cultural insights —qualitative input— that triggers its relevance, underlying the rules of engagement for brand conversation behind each Twitter hashtag.

This exciting journey of collaborative research and strategic thinking showed us once again that the most strategic way to create value in the Big Data world relies on the ability we researchers have to link it back to the cultural and human needs the data is based upon.