We all enjoy feeling special and appreciated – whether it is
in our relationships and friendships, at our place of work, or when we are
interacting with a business. This
is the reason why brand personalization is such an important tool that
companies are using to connect with their audiences.
Personalized experiences have revolutionized the way
consumers engage with brands and make purchasing decisions. If a business
offers personalized experiences, customers are over
four times more likely to convert – and they tend to spend up
to five times more than the average consumer.
Clearly, personalization
is important to online shoppers, and most businesses realize that they
need to find ways to customize their interactions, particularly through digital
marketing. However, many are finding it quite challenging to keep up with
customer demands in this regard.
Since customers are quite aware of the fact that brands are
tracking their every move online and keeping record of their data, they expect
personalized perks in return. However, some personalized marketing methods are far more
effective and influential than others. Customers are no longer impressed with
simple touches – like an email with their name included – they expect
businesses to understand exactly what they want, and when they want it.
Thankfully, AI technology is not only making it possible for businesses to meet up to their customer’s personalization demands – it actually makes it quite simple, thanks to automation.
Without further ado, here are three ways Artificial Intelligence can be your personalization game changer!
1. It Makes Deep Audience Analysis Simple(r)
The real secret to effective customer personalization is
having a deep and clear understanding of exactly who your customers are and
what they want.
Obviously, the only way to do this is through data-driven
audience analysis. AI can be incredibly useful for helping to drudge through
large sums of consumer behavioral data and connect the dots to understand what
it all means.
One rather interesting example of this actually comes from Hollywood.
Movie
studios are now investing in AI technology to help them create
the next blockbusters by analyzing their audience and predicting the types of
movies that will do best.
20th Century Fox recently used advanced vision
systems with AI algorithms to analyze the audience’s reaction to a trailer and
determine the exact frames that elicited the most positive reactions. This is
known as “Project Merlin.”
The studio uses the Cloud Machine Learning Engine in conjunction with the TensorFlow deep learning framework. Merlin scans a movie trailer and labels certain objects and how long they appear on screen – as well as how it all correlates to the film’s genre.
For instance, if a trailer has a longer, close-ups of a
protagonist, the film is more likely to be a drama as opposed to an action
movie.
This data is then compared to the elements found in other movie trailers that got rave reviews. The data is then used to help predict the types of movies that various audiences would be most likely to see (and ideally) enjoy.
Where to Start with Audience Analysis?
In order to truly optimize the customer experience online,
you need to first understand who is
using your website, how they arrive there, and what they are using it for.
AI-powered analysis programs can be used to break down your website’s traffic
data for a clearer audience overview.
By using provider information and IP addresses, these
programs can show you exactly where your customers are located and how they are
arriving to your site (such as via organic search or a PPC ad).
You can also break down the number of new-versus-return
visitors and help you track targeted accounts to monitor behavior and
interactions.
This kind of in-depth audience analysis is the critical first
step to effective personalization for several reasons. First of all, different
demographics and groups will have varying preferences on the kinds of
customized experiences they want from your business.
According to Adobe’s Digital Advertising report, younger age groups are far more receptive to personalized details and open to more of their data being tracked than Baby Boomers.
You need to know the makeup of your own specific audience in
order to determine the level of personalization that will resonate best with
your customers based on details like their age, location, frequency of
purchase, and position in the buyer’s journey.
Secondly, access to this kind of
information can help you understand the motivations behind your customers’
behavior and how it varies from segment-to-segment. This can be surmised by the
path that they follow from the initial link that leads them to your website to
the moment they exit. Look for correlations between behavior and demographics.
For example, are business leaders and
customers in higher positions more likely to consume your blog content and
arrive via external links? Are repeat visitors returning through organic
searches or by targeted clicks, and do they tend to head straight towards a
conversion on their second or third visit?
By using deep-analytical programs, you can start to truly understand who your audience is and how to influence their behavior by leading them towards the content that will motivate a conversion.
2. It Allows You to Conduct Multiple A/B Tests Simultaneously
Chances are that you will not get your personalization
marketing strategy right on the first try.
Just like any other business practice or marketing strategy,
you will need to monitor and test it along the way until you find the methods
that make the biggest impact on your customers. In order to optimize your
website, you will need to run A/B tests to find the layout, structure, and
content that bring in the best results.
The traditional approach to A/B testing can be extremely
time-intensive – because you are only testing two design elements against each
other at once. While this may work just fine for things like blog titles or
color schemes on your website, it is not necessarily the best approach for
finding the optimal personalization mix.
AI streamlines the testing process as it is able to measure the results of multiple variants simultaneously. The currency exchange provider Monito used AI when they were developing their website to optimize the design. AI allowed them to test twelve different design tweaks at once – which meant that Monito gathered enough results for a final decision in a matter of weeks, rather than months.
Where to Start with A/B Testing?
The first thing you should do in regards to AI A/B testing is
to learn more about it and determine whether or not it would actually make a
significant difference in your testing process.
The major advantage of AI in this type of testing is its
ability to compare many different variants at the same time – as opposed to
just a small handful. This puts you in a better position to predict which
designs will have the best results in terms of engagement or conversions.
There
are all kinds of psychological nuances that go into the process of getting the
human mind to click; you don’t want to leave any stones unturned in your
testing program!
Start by creating a list of ALL the possible variants that
you want to test to optimize your website or UX.
- Are there various colors that should be adjusted?
- What about the layout?
- CTA placement?
- Menu design?
- Should information be hidden in dropdown boxes or displayed on the homepage?
- Where should the search function be located?
From there, you need to decide whether or not an AI-assisted tool is actually necessary. There are plenty of multivariant testing programs that do not use AI – this technology is really a complimenting feature that helps these programs to work better and faster.
3. Creates Opportunities for One-on-One Connections
The main point of personalization is to make each customer feel special and unique. This is what builds meaningful connections between your customers and your company name. When people feel like a business really “gets them” and cares about their wants and needs, it builds an emotional connection.
It’s a great thing when consumers feel an emotional tie to your brand because it tends to influence their loyalty and advocacy in a positive way. But for larger companies, it can be extremely difficult to make each and every customer feel appreciated on an individual level.
Where to Start with One-on-One Customer Personalization?
Deploy is designed to help businesses personalize their webpage layout based on individual account information or other advanced targeting options.
You can see an example of how this could be done from Savi – a sensor analytics company. They service both government agencies as well as corporations, and their homepage layout will automatically adjust depending on who the website visitor works for.
CRM tools like Affinity are designed to track all of your audience’s consumer data and provide intricate reports to help them understand their preferences and behavior even better with ABM (account-based marketing).
Affinity uses AI to analyze all of your customer accounts and predicts which ones should be targeted based on their position in the sales pipeline.
The program is also designed specifically for relationship
management. It keeps track of all of the important details and connections that
your sales and marketing team can use to personalize experiences and close more
deals.
Access to information like this is especially important for
B2B organizations. They can see exactly how everyone within a business is
connected and who they need to reach out to next for the best results.
For B2C, this type of relationship management can be used to track past interactions, record important information, and use for more personalized communication.
Conclusion
Personalization is without a doubt going to become even more
influential over consumers, so businesses need to focus on perfecting their
strategies for their exact audiences.
By using AI in this regard, companies will find it far easier
to pinpoint the exact strategies that will help them connect with their
customers on a deeper level and provide a customized experience that impacts conversions.