Sites like Amazon and search engines like Google use machine learning (ML) to learn from user behaviour, in an effort to make the experience align with the behavioural actions of the end-user. The system basically identifies customers’ needs and wants based on what they do. The system then evolves and changes to create a better user experience (UX) for the end-user.
We essentially do this manually with SEO when restructuring on-site environments to suit our target end user based on their behaviours. For example, if 80% of users on the Sales-Promotions website visit the cashback campaign page, then it makes sense to move this page to the front of the website to create an improved UX.
Machine learning means that sites and software are now performing these tasks without human input. Systems are now gathering data and changing user experiences based on overall user and individual behaviour. At the moment, Google will display search listings based on sites you have previously visited, your location and your individual brand/product preferences. Advancements in machine learning could see results being displayed based on factors like affordability and even intrinsic personal preferences such as colour preference and preferred style of products.
In terms of SEO, companies must begin to investigate future-proofing SEO strategies to take these advancements into account. Indeed SEO is possibly a dying role as a human operation and a skilled manual function. SEO can be co-ordinated much more efficiently with a machine learning system that will essentially action SEO in a far more productive way than a human can. There will be the argument that a mixture of creativity and unique problem solving capabilities of the human mind will always be needed to give the top positioning strategies the edge. But ML is forecasted to replicate these qualities essentially leaving us humans obsolete in the function.
1. How do you prepare for machine learning?
There is no definite answer to this as the development of machine learning will take many directions as it evolves. In our humble opinion, we can expect search algorithms to take more personal factors of a user into account; as mentioned, affordability, colour preference and shipping preferences, with an ever-growing list for different industries.
In an example of a customer booking a restaurant table on a website, maybe the future machine learning search engine algorithm understands personal user information such as allergies and user food preferences when presenting websites, which it learned from the user’s online activity. Then it takes into account the number of people for the table from previously booked tables at restaurants online. It then ascertains if there is a specific data trend and will present the search engine results based on high probabilities. Such as estimated guests for the booking, affordability/spend habits of the user and travel distance of diners.
In this case, in terms of SEO, it would be a good idea to start highlighting table capacity on the website. As well as the menu with prices and allergy alternative options. At the moment, users will generally not search a restaurant based on table size. But search engine machine learning will increasingly take all of these factors into account when presenting results.
It is estimated by Google that voice searching will be 90% of how we search in the year 2020. Personally, we think 50/50 would be a safer bet. Whatever the figure will be, it means that voice search needs to be taken very seriously in terms of creating our future SEO strategies. In terms of PPC, long tailed keyword strategies are now a must to cater for this evolution in search behaviour. This behaviour also allows machine learning to take other factors, such as tone of voice, into account. It could also take a user’s current mood into account based on how they sound when performing the search request. Search personal assistants such as Siri, Alexi and Cortana have made massive strides in completing close to an actual conversation with the user. They add a real human dimension to the face of this evolution in technology.
VR will also present a whole different ball-game in terms of UX and interaction, and the requirements in terms of how people seek information. We strongly believe it will change the way in how we conduct our daily routines and VR will become paramount in the future. Imagine, websites may be online stores that we enter and walk around and interact with sales assistants. Virtual shopping cities with everything you could ever need. The benefits of shops moving to this environment would have big impact on staff commuting to work which, of course, benefits climate change.
The only way to prepare for this technology is to become a fan and understand every new development. So that you are ready to join the revolution when the time comes. It is very important to understand that a market will lag behind the development. Especially in technologies like VR, so don’t jump before you look.
2. Planning for the future
At this time, it is impossible to secure a certain strategy that will nail machine learning future planning. We can rest assured that companies that take educated risks and win, will top search rankings in the coming years and reap the benefits. It all really falls back to the golden rule of marketing. Start with the customer and work your way back by providing them with every essential factor of their intended experience.
3. Machine Learning – Exciting or Scary?
Machine Learning is another step on the path towards advanced AI which is both exciting and scary. Big brains such as Stephen Hawking and Elon Musk have warned that AI is the biggest threat to human existence above meteorites, war and disease. Their point being the stage of realisation (commutation) with the machines that, actually, humans are the weak link in the whole operation. They then employ a disk clean-up and lose us in a Terminator-esque approach.
No need to join the resistance in defeating SKYNET just yet though. The more likely development rather than our termination will be the merging of human biology and technology. Biological machining. Think of the accessories.