How To Hyper-Personalize Your Marketing Campaign

The math continues to speak for itself! According to a startling 80% of business owners who participated in a study by the customer data platform Segment between April and May 2022, customers spend not less than 34% more on average when their experience is personalized.

However, the stakes go beyond that. Focusing intensely on your client's needs is no longer just about what you stand to gain as a business; it's also about what you stand to lose.

Customers appear to be becoming more conscious of, and leaning toward brands that prioritize integrating granular contextualization into their customers' journeys. If the experience wasn't sufficiently tailored, 60% of consumers said they would switch brands.

With these and other stats and how they've progressed over time, it's becoming clearer that personalization, as we've known it, is about to move several floors up. Simply addressing a customer by their first name is no longer enough. Neither is knowing what the market segment they belong to might generally want. The brands that will stand out in 2023 and beyond will be able to leverage data to understand the preferences and needs of each of their customers while ensuring privacy.

Rockier terrain? Yes. But fear not, there’s always a way around it.

A few key steps can help you transition from simple personalization to hyper-personalization in your marketing campaigns. But first, let's dig into what hyper-personalization is. How does it differ from good old personalization?

Hyper-Personalization Defined

Personalization and hyper-personalization are not the same things, to put it simply. Despite the fact that the former is the seed that gave birth to the latter.

When it comes to your marketing campaign, hyper-personalization refers to your capacity to combine behavioral and real-time data collected from various channels, touching on clients' various and specific touchpoints, to build a "hyper-focused" campaign (on an individual level).

As a result, a company's conversion potential is multiplied because it is no longer just attempting to predict or anticipate group needs but is also working to learn what specific customers will want and when they will want it. This includes being aware of the elements that will probably affect each person's purchasing choices!

So did they hold off on purchasing a red coat they liked until your store had a sale on a particular Monday last year and then come to your store with coupons? Did they click on a link you sent them via email or did they find you on social media?

Personalization means you will include this and other customers who bought coats from you the previous year, in a broad marketing campaign. Hyper personalization, on the other hand, is even more precise. It will dispatch an ad targeted at this specific client on a Monday, during a sale, and possibly mention how they can use a particular coupon to make their purchase. You send out this ad around the same time of the day they found time to look at your offer last year.

Artificial intelligence, IoT, and machine learning will assist in curating a list of coat options that are similar in taste, color, and so on, to the client's previous purchase.

A little more complex but many times more effective!

How Can You Hyper-Personalize Your Marketing Campaign?

Now that you have a solid understanding of what it is, it's time to learn the essential components that will enable you to maximize the impact of your efforts at hyper-personalization.

For an effective plan, make sure of the following six points:

1. Data Mining

The quality of your data will determine the accuracy of your personalization, so you'll need to have gathered the correct data type.

You want to segment down to the granular level, and your data will need to light your way here. Your offers will be refined, and you'll send them to the right people at the right time, improving your conversion rate.

To get hyper-personalization right, your machine-learning algorithm will need at least the following data points to work with:

Quantitative:

• Their activity on your website, such as what they are subscribing to, products they are viewing, how many times they came to your site, and other critical website activity.

  
  

• What can you learn about their preferences from their social media activity? Do they have profiles on Facebook, TikTok, Twitter, Instagram, etc., and if so, what content and pages are they engaging with the most?

  
  

• What problems have they raised with customer services if they have contacted them at all

  
  

Qualitative:

You'll need to pull out your questionnaire forms and get into survey mode for these ones. Your questions will need to capture the opinions and attitudes toward your brand or product. This data will help you predict whether a customer will repurchase or figure out anything that's stopping them from buying.

Descriptive: This is non-numerical information that can help you learn more about the customer. Examples include:

• Their occupation: what's their field or job role
• Their habits: when are they likely to be online, and on which platforms? Will you need to customize their content to the device they use? Do they tend to complete their purchasing journey in one sitting, or do they leave products in the cart before finally finalizing a transaction?
• Lifestyle: do they live in a house or an apartment? Do they use public transport or drive a car? What make or model if they have one? Are they into plants, pets, etc.? Are they single or married?

2. Customizing Your Offer

Your customers don't spend their daily lives waiting to transact or, worse yet, want to be understood only to the extent that they can. They are people with aspirations, problems, passions, preferences, etc. They likely choose their friends based on some of these things. And now, in the sea of internet options, they have the freedom to be just as selective with the brands they buy from. Brand-customer compatibility is rising in value, and you'll need to invest in it for your business’s success.

Most customers will be more willing to engage with only those offers that correspond to the products they previously bought on the same platform. You don't need much to start, you can scale as you go. Begin with segmenting by age, gender, etc., and then further by the products and times that customers are consistently purchasing. Aim to get it right, down to the factors that seem to influence their buying decisions the most, then leverage on that!

3. Personalizing Your Messaging

In line with this, creating hyper-personalized messaging will require you to use advanced marketing software that supports this. You'll be able to create detailed and contextual campaigns that make use of the following:

• Contents that adjust to the time and place they have opened
• Stock-keeping units (SKUs) that adaptively change as soon as a product is out of stock
• Real-time or dynamic pricing
• Products a customer previously browsed on

4. Take a Multi-Channel Approach

Remember how we stressed earlier about how your customers are complicated human beings? In this same vein, take into account the different responses people might have to your messages across various platforms. Interacting with your brand on Instagram can mean that you find them in a particular mood(perhaps a more relaxed one) than you would on LinkedIn or email. Your data will help point toward this kind of information.

You're best prioritizing the platform they have interacted with you before, but even that will not always be enough as you'll still need to use all the other media to increase your chances of landing the customer.

5. Timing

As the amount of data businesses collect continues to grow exponentially, even those that prioritize first-party data can struggle to process it manually. However, there are several options available to businesses looking to optimize their engagement strategies and deliver the right content to their customers at the right time.

One effective approach is to leverage automated marketing platforms and predictive analytics. By using these tools, businesses can narrow down the best times for engaging with customers and increase the likelihood of conversions. This approach can help businesses make the most of the data they collect and drive more effective marketing campaigns.

6. Multivariate Testing

Chances are you've already read a lot about A/B testing, and even if you haven't, it's very easy to find out what it's all about. But despite all the fanfare, it isn't the testing method you should depend on for hyper-personalization. This doesn't imply ditching it all together but rather digging deeper than it.

A/B testing is good for testing between two or more radically different offers or campaigns. But once you find which of the offers is your global maximum, or the one that's converting the most, then it's time to test for a local maximum, and for this, you will have to ditch A/B testing for multivariate testing. To do this, your approach will need to get more complex across multiple different elements of your winning offer. What variables can you tweak and test until you find the exact version that you will use within various specified contexts?

A/B testing is useful for comparing two or more offers or campaigns that are very different from one another. But once you determine which offer has the highest conversion rates or is your global maximum, it's time to test for a local maximum. To do this, you will have to ditch A/B testing in favor of multivariate testing. Your strategy will need to become more complex across multiple different elements of your winning offer. What parameters can you adjust and test until you discover the precise version that you will use in various specified contexts?

Bottom-line

A new era of more predictable conversions has arrived, and you're not too late if you start working out what works best for your business now. In fact, you'll most certainly be one of the early adapters and potential trendsetters of this new e-commerce best practice.

The ability to get perfectly timed offers, and intuitive store experiences that anticipate their need and allows them to be in and out of an online store in a few minutes is the frictionless experience your customers are waiting for and for which they may be willing to pay more and stick with you! Bonus points if you're investing in first-party data because as the internet evolves into Web3, the cookie will crumble indefinitely- saying goodbye third-party data!