Last week, Amazon announced that its machine learning service Amazon Personalize, which is focused on helping developers create individualised recommendations on their platform for their users, has now become generally available – although initially in certain regions only. This is a huge opportunity for companies who wish to bring a more personalised approach to one or more parts of their business, which according to research, is definitely something that companies should be focusing on more as they look towards the future.
Personalised content has become a huge part of today’s online experience. Service users and online store customers have already become accustomed to personalised recommendations that help guide them to content and products they are more likely to be interested in, based on data gathered about an individual’s usage on a website or webstore. However, this does not represent the full extent of possibilities that personalisation offers. On the contrary, personalisation can be implemented in other business areas as well, which opens up a whole new world of opportunities.
For example, it is possible to implement personalisation in smaller details, such as information panels, as well as on a larger scale, such as by creating a fully personalised user experience or a personalised sales experience, e.g. for flight or bus tickets. Another area where personalisation could and should definitely be used more, is marketing. The time of basic personalisation has already ended, a fact that was already proven last year by Pure360, whose research found that only 8% of customers are likely to engage with marketing material, such as newsletters, that addresses them by name. This means that companies should endeavour to create more personalised marketing content if they hope to catch the attention of the other 92% of consumers. To further bolster this idea, SmarterHQ found in a survey they conducted that 70% of millennials are frustrated by companies who send them marketing emails that are irrelevant to them.
Only 8% is likely to engage with marketing material that addresses them by name, and 70% of millennials are frustrated by companies who send them marketing emails that are irrelevant to them.
A huge impact on revenue
Detailed and in-depth personalisation also yields incredible results in terms of revenue. Barilliance found that in the case of product recommendations, the AOV or average order value multiplies by 369% when customers engage with a single personalised recommendation. Even further, that value was seen to continue growing for at least another four clicks. They also found that these kinds of personalised recommendations also helped increase customer conversion, with an increase of 288% after the first interaction.
Accenture also conducted research on personalisation and found that a staggering 91% of consumers are more likely to do business with brands who remember them and provide them with only those offers and recommendations that are relevant to them. Another significant fact that emerged from the study was that 48% of consumers admitted to leaving at least one online store because they felt that it was badly curated to their needs. As noted in the results, this number has grown over time, indicating that companies have not put time and effort into creating a personalised experience for their customers.
91% of consumers are more likely to do business with brands who remember them and provide them with only relevant offers and recommendations
Data gathering in the era of GDPR
Of course, for companies to be able to incorporate personalised experiences into their business, they need to have access to their customers’ personal data. But in a time of laws such as the EU’s GDPR, how much are consumers willing to share such information?
SmarterHQ found that although consumers feel like companies have too much information about them, 90% are still willing to share behavioural data in return for a better experience with the company.
The good news is that companies are starting to really understand the importance of personalisation. A survey conducted by Evergage shows that nearly all marketers believe that personalisation is key to good customer relations. However, only 12% say that they are satisfied by the level of personalisation they have currently implemented. At the same time, 55% of them mentioned that they do not have enough data for proper personalisation. It was also found that on average, customer data relevant to personalisation is kept in four different systems.
Although all marketers believe that personalisation is key to good customer relations, only 12% say that they are satisfied by the level of personalisation they have currently implemented
The path to personalisation
But how would a company who has never done personalisation go about setting it up? In the case of our clients, for them to be able to implement a service like Amazon Personalize, the first thing they would need to do is ensure that they have the data required for personalisation, such as clicks, signups, page views etc. Generally, online stores or websites that implement some form of self-service will already have this type of data gathered in one place. However, if a client has the data but it is not easily accessible – for example, if the data is spread out across old and new systems or, as was the case in Evergage’s survey, the data is kept in multiple systems – then the first step would be the creation of a data lake along with data processing solutions to help aggregate the data and process it in a suitable way.
Once this data is available for use, it will be combined with whatever the client wishes to recommend to their customers, e.g. products, videos, articles and so forth. If the client wishes to, they can also specify further demographic information about their users that they wish to incorporate into their personalisation. Amazon Personalize can then process all this combined data to identify the meaningful components in it and apply suitable algorithms to it, resulting in a personalisation model that is customised specifically for our client’s data. This model will then help our client reach the coveted next level of personalisation that consumers worldwide are looking for when interacting with brands online.
Amazon Personalize processes data to identify the meaningful components in it and apply suitable algorithms to it, resulting in a personalisation model that is customised specifically for our client’s data.
In cases where a client does not have the data required for personalisation at all, we at ADM Group have different units dedicated to helping our clients determine the best way to start gathering the necessary data. The purpose of this is to help make the process of implementing personalisation easier for our clients and once that has been set up, to help them grow their revenue which, as seen from the above-mentioned research, can grow immensely from this.