Three key ways predictive analytics can improve social performance

AI is gaining significant readership. Businesses of all sizes, all over the world, are becoming conscious of the rise in AI in the marketing field. Why is this happening? Put simply, every single business needs the same thing: getting clients. Reach an audience, the right one, and sell. No tricks on that.

All executives know that to be profitable companies need to sell – but over the last few years they are facing a continual decrease in their ROI. Marketing and sales strategies are less effective than in the past – and they need to search for ways to improve.

Predictive analytics is rising above other technologies. It promises to provide better assessment testing content before going to the public. Predicting before publishing. Studying the impact for each different segment. Saving money and workforce time. Here, we explore three ways to use predictive analysis to improve social performance through dynamic buyer personas, keywords contextualised about topics and segments, and ads impact prediction.

The use of predictive analytics

The most beautiful stories are those in which we find a piece of ourselves. For this reason, the biggest brands are looking for the right tone of voice, the themes, and the words to involve their followers on social networks. The clearest example is that of a blind date. How can it be successful if we do not know anything about the person we are facing?

This is a real problem. It is not time to be shy.

We don’t need data, because we already have it. But we have historical, unstructured data. So the first step is to organise and segment; transforming unstructured to structured data, to let it become useful.

Think of it as Lego bricks. If bricks are coming from different packs, you have to figure out what to do with them. You will have so many options that you stay puzzled, and you will go ahead by uncertain procedures. This means you are going to spend a lot of time on pieces recognition, mounting, dismounting, trying again. However, what if they are organised in packs by theme? You know that they are part of a defined shape. Sure, you need to test, but you already know that all the pieces are part of what you want to build.

Predictive analytics is the use of data that allows selecting the right pieces to build your Lego figure in one click, based on statistical algorithms and machine learning techniques. Predictive analytics is this set of data analysis that can tell you how things are more probably to go according to historical data.

Let’s repeat: predictive analytics says what will happen in the future, through data and a bunch of unique statistical and machine learning algorithms. Sounds helpful? It is. More than you can see at a glance.

How predictive analytics impacts marketing activity

On social networks, people talk, get angry, get excited. Understanding the audience is everything in the marketing arena. It allows us to approach the right people with a focused strategy. So how can a customer-centric approach be improved thanks to artificial intelligence?

The ability to acquire essential information about people is just one of the benefits of AI in social media marketing because the data, as we said, is already present. So as a result, the potential applications for social marketing are infinite:

  • Dynamic buyer personas: Customer profiling – habits, interests, words – are essential for the success of personalised campaigns. Old buyer personas are just a snapshot resulting from a historical moment. Dynamic buyer personas are the result of continuous social interactions

    As a result, there are no more ‘buyer personas’ per se – but a dynamic audience to engage. This can be translated into targeted strategies. Thanks to valuable information and predictions about sentiment and attention, marketers can concentrate on creativity and budget on reaching a higher quality of the conversation.
     
  • Contextualised keywords: AI contextualises keywords according to topics and segments, so you can better understand what people have in common. Keywords and hashtags now have a real meaning in the context where they are.
     
  • Ads impact prediction: The clean, organised and recombined information allows us to make a prediction, to attract and convert, to give the community what it seeks. A prediction is out of control just because people do not know what they want. We need to find profound reasons that go beyond words, but that emerges in behaviour. Hence the AI. It is excellent to reveal common points to behave apparently without a relationship.

Conclusion

Studying the natural language of your market will be the fuel of any effective marketing campaign to create meaningful engagement with your best audience. Why the best audience? Because the AI tools will have selected and segmented the total to go to the specific. Better focusing means a higher personalisation level and effective prioritisation of your content pipeline.

AI can assist with segmentation and prioritisation of content and leads to achieve higher results, make marketing campaigns smarter, cost-effectively addressing the right people, while marketers can present social media users with more relevant experiences.

This may sound great – but if you are wondering what this means for human creativity, don’t be scared. Humans are still at the base of the process; they are just now in a different position.

Interested in hearing leading global brands discuss subjects like this in person?

Find out more about Digital Marketing World Forum (#DMWF) Europe, London, North America, and Singapore.  

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