Lovemarks: the strategies to make users fall in love with your brand

The Intelligence of Love: Social Media Intelligence + Content Intelligence

Antonio Cabras
Marketing&Digital Consultant @Sinfonia Lab

What is a Lovemark

The "father" of this term is Saatchi&Saatchi’s Kevin Roberts: it indicates an affective relationship based on love and respect, which is destined to replace the idea of brand itself.

Emotional components come into play: the bond with the consumer is something much deeper than the simple offering of a product/service. As Roberts said, brands belong to shareholders and managers, lovemarks belong to people.

Talking about love for a brand may sound a bit of a stretch, if we consider the brand as a mere supplier of goods. But if we take a closer look at our own buying behaviors, we’ll see that our choices are influenced by how we feel towards a brand. 

After all, while reason leads to conclusions, emotions lead to action: this impulse, driven by love and respect, brings measurable commercial benefits.

 

How a love story is born

 

But how can we make our consumers fall in love with us?

Any first contact requires listening, an activity full of enthusiasm for the discovery, but also taking effort to open up, to enter a mood of harmony and intimacy.

Assuming that business is a trade of values, the use of a Value Proposition Canvas can be an excellent starting point to understand the needs and desires of your customers. It will help you identify their real needs, and to connect them with the values your company can offer.

Well, that’s certainly true on a theoretical level, but you’ll need the right tools to put it into practice. In fact, there are three necessary steps in the process of understanding your user:  

1) Listening: selecting and extracting the right data

2) Analysis: processing and integrating them with the information already in the possession of your company

3) Output: gain insights to guide decision-making processes 

 

The right Intelligence for you

 

With the advent of web 2.0. and the possibilities of interaction offered by the Net, the amount of data has increased exponentially. We’re talking about the so-called Big Data, which is mostly unstructured data coming from social networks

Just think that 95 million photos and videos are shared every day on Instagram, 6 million tweets per second on Twitter, and over 500 thousand comments per minute on Facebook. 

Data monitoring is no longer enough (there’s just too much of it!). We need to take a step forward and make sense of these huge amounts of data collected daily, to extract insights useful to make informed business decisions

That’s where Artificial Intelligence (AI) comes in:  

- Social Media Intelligence

Artificial Intelligence can analyze large amounts of social listening data, instantly identifying topics and trend patterns. In this way, it is possible to find out which are the weak points of your online presence and to identify the opportunities to invest in.

You’ll obtain AI-powered analysis about volumes, sentiment, personal information, trending content, purchasing behavior, devices used, flows, surveys on the audience, etc., which can prove very useful to your business. 

How do you do that? Here some examples: 

  • Competitive Intelligence: monitoring and studying competitors helps strategic analysis and positioning
  • Social Adv Targeting: identifying the portions of your audience with the highest response rates, according to the interests and needs detected. 
  • Social Lead Generation: new audiences can be found through brand awareness, on the go conversion and PR (e.g. selling a travel insurance on the fly to users who are about to leave on a trip). 
  • Crisis Management: content analysis detecting and alerting about flames, allowing you to develop defense and prevention strategies. 
  • Influencer detection: macro and micro influencer can be identified, to integrate your marketing strategy with ad hoc digital projects, online and off-line events. 
  • Content Strategy: by studying models and trends you’ll be able to define your buyer personas, your content and tone of voice, plan and verify your social editorial calendar. 

…and so on, to implement customer care strategies, CRM enrichment, prediction analysis, risk mapping, churn prediction and many others. 

- Content Intelligence

Content published on proprietary channels (website, e-commerce, blog, etc.) can provide companies with decisive data on the interests of its audience

To make content receiver of information, you must first proceed to a rationalization of your company’s entire library: all the brand’s digital assets, including algorithms (speech-to-text, semantic analysis, image recognition, etc..), will be classified by AI with tags describing them. 

Thanks to the matching made by algorithms, when a user interacts with a piece of content AI will infer their interest from the tags and populate their CRM profile (this also applies to anonymous users). In this way, you’ll have a real-time snapshot of your audience preferences (topics, formats, channels, etc). 

In conclusion, we can affirm that the joint use of these two strategies helps brands create an increasingly significant relationship with their audience, who feels loved and ready to reciprocate.