One of the global leaders in AI, Google, is using the technology to create consumer-centric interaction using data points to identify intent and passion, writes Katie Sterling

As consumer behaviours are increasingly complex AI has an integral role to play. According to Samuele Saini, Head of Strategy and Insights at Google Singapore, its “company proposition has moved from mobile-first to AI- first”. They now look towards machine-learning as the core route to re-thinking everything they are doing, the audience at the MasterCard Innovation Summit 2017 (Singapore, September 2017).

Saini cited that Google used to run a survey around how many times people were online (E.g.: once per day, 2-3 times) but had to stop asking these type of questions now, as people check their phones 150 times per day. In actuality what matters is what consumers do when they are online and how machine based learning can bring you closer to understanding changing behaviours.

“If you look at where consumers were 5-10 years ago demographics and location were the targeting options for a TV campaign. You just needed to know you are in Singapore and aiming for a certain age group and that was the way for a brand to reach consumers”.

Nowadays, that complexity has completely exploded.

“You have to consider what’s the connection (is someone on a mobile connection or are they on wifi), what else are they browsing, what else are they watching, what’s the time of the day, what’s the location, what apps are they using”. The number of factors under consideration is vast and complicated by comparison (see below).

As a result at Google “We do not think of big data – because data is big by definition” and machine learning (a method of artificial intelligence) has become essential. In fact, Saini said “It is already powering most of the solutions you are using”. As an example, the suggested reply on Google Mail is already being used daily and getting smarter and smarter.

The search business, which remains at the core of Google, has transformed drastically too. There used to be a time where we used to manually bid on key words, but all that is now gone with machine taking over. Search is being completely renovated in a way to make it scaleable and useful as a system via AI (see below).

Furthermore, when it comes to improving consumer-centric interactions (from both and end user and partner perspective) there are three clear types of opportunities that are opening up:

  • Personalisation: Using first party data to reach your existing customers in a more meaningful and targeted way. For example, if they are light customers and have not come back in past few months what’s the right message for them? Or if they are loyal and power-users how do I cross sell and upsell by presenting services in right way?
  • Intent: Helping decide on the behaviours that classify a person as ‘in-market’ for something. This is about distinguishing more precisely intent from passion. Some people might be online looking at cars all day as they love them, but are not in a position to actually buy one. Recognising intent is highly relevant when it comes to efficiencies. For example, what are the identifying factors and user behaviours amongst those that are just about to apply for a credit card?
  • Passion: Thinking about taking the previously used term of affinities (looking at groups that share an affinity – such as movie lovers or shutterbugs) a step further. Passion is instead focused on connecting with engaged audiences based on a more detailed picture of their behaviours. This is the opportunity to connect by building a more granular, zoomed in view. For example, are they a fan of Korean drama? Or Bollywood movies?

Machine based learning has completely changed the approach to problem solving. Its success is based on the ability of the system to recognise and these examples are still based on traditional interactions, however, voice assistance and photo recognition will change this even further – the impact of this progress will soon become apparent. 

“We are often over-optimistic about change in the short [term] and under optimistic about change in medium term but AI is something that is changing fast”.