Personalization has been an important factor in online marketing success for quite some time. With the development of CRM software in the 1990s came the ability to use customer data – such as name – in marketing messages, and send communications based on previous interactions and preferences.
While this method of marketing using customer information stored in a database continues to be used today, personalization started really evolving with the emergence of social networks in the 2000s.
These platforms are able to collect a huge amount of data about their users and were instrumental in the development of software and tracking tools to use this information for marketing purposes.
We’re now entering a new era of the Internet of Things and Big Data, which will expand the possibilities of personalization in marketing messages even more. One of the most exciting technologies impacting personalization that is advancing at a rapid rate is artificial intelligence – bringing new opportunities and possibilities to consumers and marketers alike.
Old-style Personalization and its Limitations
The old method of personalization was based on a set of rules based on existing data. So you might greet your email subscribers by name but show them all the same content, or program your e-commerce website to display prices in dollars for visitors from the US and pounds for visitors from the UK. This can be very effective, but treating large groups of customers as essentially the same does have its limitations:
- Data must be collected first – there’s no personalization in real-time. You need to look at a decent sized set of data and make decisions based on that data, which can take some time.
- Personalization is pre-programmed, not automatic – marketers have to do the work of deciding what content to show to which visitors, instead of the computer working out the optimal version for each type of visitor.
- Segmentation is limited – with this old style of personalization, it’s just not practical to attempt the granular level of segmentation that’s possible with today’s AI-driven personalization software. You might adjust your content slightly to cater for existing vs. new customers or different age groups, but coming up with thousands of different variations based on demographics, past behavior, browsing history, and other factors is pretty much impossible.
- Users must be logged in to see personalized information – in old-school personalization, the data comes from the user database, meaning the user must be logged in to see personalized product recommendations for example. Personalization data only comes from the database and is restricted to your own site. In the new style of personalization, data can be gathered from multiple websites and sources with tracking cookies and content can be personalized without the user explicitly logging in to your site.
The Possibilities of AI-Boosted Personalization
Predictive personalization uses data analysis and profiling tools to adapt content in real-time to optimize conversions automatically. This enables much more complex personalization powered by machine learning algorithms.
For example, a travel company could use customer data about previously booked flights and hotels, browsing history, and activity on social media to predict locations that are likely to appeal to each individual and the type of activities they might be interested in (adventure activities, spas, family-friendly excursions) and send out tailored marketing messages based on this data.
This type of personalization goes beyond even highly targeted “micro-segmentation” to achieve a unique offer optimized for each individual.
The real-time power of AI also means it’s possible to adapt and trigger automatic marketing messages in a way that’s never been possible before. For example, geo-location services now mean that as well as knowing a customer’s demographics and where they live, you can also know where exactly they are at any point in time. This data can then be used to trigger location and time-sensitive marketing alerts such as a special one-day-only offer when they’re close to a particular store.
The Future of AI in Personalization
This rapidly progressing field is being used for new and innovative applications all the time and we can only guess at how the changing face of marketing may look a few years from now.
Some companies are already using AI to drive personalized product development, such as the supplement company Nutrigene, who will send you tailor-made liquid vitamins based on your lifestyle and DNA.
If Nutrigenics sounds a bit far-fetched, this type of personalization has applications in less technical products too, such as this bot that is automatically generating product pages for phone cases (although it’s clear from this example that the technology still needs some refinement!)
Algorithm-driven design tools can also be used to customize and personalize the user experience automatically, working with human designers to optimize a design and personalize the UX making it not only easier for each individual to use, but also more likely to convert.
How to Start Using AI-Driven Personalization
Nobody knows exactly what will be possible in the future, but it’s certain to be driven by data. For this reason, it makes sense to collect as much data as possible now, even if you can’t use it straight away.
Tracking tools like Google Analytics, social media platforms, and customer reward programs can all be effective ways to collect data, but they can only do so if you have the software installed and are using them now – so don’t delay another day if using these platforms is a task that you keep putting off to a future date.
Tools like concured enable you to harness the power of AI to customize your content, delivering exactly what your customers want, on the channels where you’re most likely to reach them.
As Big Data continues to get bigger and technology becomes more advanced, these AI-driven tools will also evolve and open up new possibilities in marketing.
Despite the potential that advance personalization offers, only 7% of organizations identify it as their number-one marketing priority. However, 57% of consumers are willing to offer up their personal data in exchange for customized offers and experiences.
Now is the time to start investing in these tools and learning more about the possibilities, to ensure you can take advantage of whatever is coming in the future.
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