How to Convert First-Time Visitors Using AI-Driven Personalization

It’s a norm for marketers these days to drive meaningful engagement with returning customers through personalized marketing campaigns and content. However, with marketing automation tools powered by artificial intelligence (AI), you can now personalize your website content for first-time visitors to turn more traffic into conversions.

In today’s noisy digital space, brands place high premium on personalizing their content and services to their audiences. Tailoring the content on an app or a website to match visitors’ interest can be a powerful way to convert them into leads or even buyers.

According to the 2018 Personalization Pulse Check from Accenture Interactive, 91 percent of consumers are more likely to purchase from brands that provide relevant offers and recommendations.

How Far Can Traditional Methods Go?

Marketers have so far approached personalization by researching the existing customers and refining target personas to create more tailored content over time. As you get more data on the type of visitors who return to your site or app, you get a better understanding of the creative that should be produced for these visitors.

While this helps in delivering personalized experiences for returning customers, a major portion of visitors convert on their first visits. According to a recent research, 84 percent of conversions happened during visitors’ first-time visit. This means you might be missing out by not personalizing experiences on you site to new visitors.

There are some visible attributes of new visitors you can use to personalize your site’s user experience. Traditionally, data points like IP address, location, device used and source of traffic can provide marketers some insight into what new visitors expect to see.

Geolocation filters, for example, can help clothing brands personalize their online stores to show season-themed clothing in local languages based on first-time visitors’ IP addresses. Similar first-party data points can also help surface promos, time-sensitive discounts and freebies on popular purchases from your store exclusively for first-time visitors.

How AI-Driven Personalization Can Do Better

However, these traditional methods still have limitations as they are based on information collected from user behavior within your website or app. They are also incapable of distinguishing behaviors from the same user across devices, thus losing out on opportunities for device-specific personalization.

Today, with the help of AI, you are able to understand consumers interests and behavior outside of your own online channels, which means even before visitors make their first visit to your site. So, you will have a better chance to personalize experiences accordingly.

  • Cross-device personalization

Despite the explosion of marketing automation tools in the last few years, marketers still struggle to track consumers across touchpoints like devices and channels. For example, a new visitor may browse a fashion retailer’s site on her tablet on Sunday afternoon, bookmark her favourite dress on her PC the same night and decide to check out only on her mobile later. These three interactions would traditionally be attributed to three separate users.

With a proactive marketing automation tool powered by AI, you are able to map the user journey and gain a single customer view across all possible screens, which enables you to deliver relevant messaging at the right time, such as a push notification remind her to check out on her way to work on Monday morning.

  • More accurate profiling based on interests from third-party data

In addition to this first-party data, marketers can also benefit from leveraging third-party data about a potential future visitor’s behavior and preferences on external sites. While some platforms provide syndicated online consumer data, they are usually collected from the behavior of logged-in users or through surveys conducted by a panel of selected users.

What is more powerful is an AI-based tool that can analyze billions of data points to identify patterns from across devices, to model how users behave and move between different screens. For instance, Appier’s AIQUA manages to do just this by analyzing more than 2 billion data points from its thousands of campaigns to identify user interests and keywords. You can layer such data on top of first-party data to segment audiences more precisely and personalize content for each segment on their first visit.

More importantly, such AI-powered tools go one step further and analyze the keywords within the offsite content consumed to reveal more specific interests like “basketball” and “FIFA”, instead of “sports”, or “bitcoin” and “virtual reality”, rather than “technology”.

Considering a first-time visitor to your travel site might have varying intents based on the articles he read on external sites – mere exploration, planning a safari in Kenya or a wine tour in Tuscany. Based on his interests, you can categorize him into “outdoor adventurist” or “wine lover”, and tailor the web content or offers accordingly when he first lands on your site.

While you can’t always expect your online or app visitors to convert on their first visits, it doesn’t mean you can’t increase the chances of this happening by using AI-power marketing automation tools to deliver a hyper-personalized experience.

Keep Your Audience Engaged With AI-Powered Push Notifications

Transform your app marketing with artificial Intelligence (AI), making your messaging and notification strategy personalized, relevant and customer-centric.

Did you know that around 52 percent of app users find push notifications annoying? An unpleasant experience around app messaging can easily result in a user opting out of notifications they find interruptive. Worse – they could even uninstall your app, especially if they find the notifications completely irrelevant.

The solution does not lie in completely doing away with notifications. When used wisely, these are an important element of your brand’s messaging strategy. Notifications help keep your app top-of-mind; they encourage users to open and re-engage with the app. Ultimately, a well thought through notification strategy encourages app usage, growing the lifetime value of the customer.

Effective Notifications Are Personalized, Relevant and Timely

In a world where 35 percent of notifications are generic broadcasts to all users, useful notifications are those that offer real value to customers, and are personalized, relevant and timely.

Netflix is often cited as an example of a brand that has nailed successful messaging through notifications. It only sends out notifications announcing the launch of a new season of a show that you follow, or recommending a newly available movie that is similar to others you have watched. Evidently, Netflix’ recommendations are personalized to your preferences.

To make notifications relevant, marketers must use the swathes of data that they have around user behavior, interest areas and past purchases to offer information that is actually valuable to the user. AI can enable this kind of insight.  

Using AI to Understand Each User at a Granular Level

AI is making it easier than ever for marketers to personalize user experiences, and encourage engagement and retention. It enables proactive recommendations or notifications on products, services or features that are aligned with user interests, pushing up the likelihood that they will engage with the app and complete the conversion KPI.

AI helps personalize messaging through:

Segmentation

Effective personalization starts with accurate user segmentation. AI tools can help you minutely segment your audience by enabling you to:

  • Analyze data around in-app user behavior, past purchase history, action on push notifications, etc.
  • Learn about individual preferences and interest areas
  • Detect patterns, and
  • Predict future behavior

Relevance

Use AI to also ensure the relevance of the notifications. AI tools can analyze vast amounts of user data around preferences and interest areas, and use this to recommend content that they would most likely to engage with. Seventy-five percent of what Netflix users consume is a result of recommendations that are triggered in this way, and 35 percent of Amazon’s revenues come from recommended purchases.

Solutions like Appier’s AIQUA, an AI-powered marketing automation tool, allow brands to hyper-personalize their messaging by analyzing the user’s in-app behavior and journey, and mapping this onto their interests outside the brand’s platforms. Insights from onsite-offsite user interest mapping enable a single customer view, facilitating a better user experience through relevant and personalized messaging.

Timeliness and frequency

How many notifications should a brand send out? Studies have shown that 37 percent of respondents would disable push notifications if an app sent between two to five notifications a week, while 22.3 percent of them would stop using the app.

This means that no matter how personalized or relevant your notifications are, if they are too many in number, chances are that your users will perceive them as disruptive and screen them out. Hence alongside relevance, marketers must also consider frequency and timeliness of notifications.

Here again, AI has a role to play – by analyzing data patterns around when users engage with your app, for example. This will help you send out notifications at the optimal time, when users are seen to be most responsive and more likely to take the looked-for action. For instance, marketers who use AIQUA not only use the platform to personalize notifications, but also to identify the right moment and right way of reaching each user.

Thanks to the power of AI, marketers today can ensure that messages and campaigns are based not on guesswork or intuition, but hard data. The kind of proactive personalization described here is just one way in which you can use AI to enhance your messaging strategy. When it comes to leveraging AI in marketing, the possibilities are limitless.

Personalization at Scale With Artificial Intelligence

Every consumer is different. They have their own interests, preferences and concerns. Sending the same message to every one of your customers and prospects is unlikely to win their hearts. Instead, it will only see your efforts quickly ignored and leave a sour taste in their minds.  

For marketing to be effective in any industry, you need to find a way to speak to your audience on a personal level, and using personalized techniques backed by artificial intelligence (AI) is the way to go.

Marketers’ Missing Opportunities for Personalization

It is now a common practice to use marketing automation tools to reach a wider audience, but the most obvious mistake that marketers tend to make is simply ignoring the option of personalization. By monitoring how users interact with your site, you can get very clear signals of what they are looking for, which device they use and at what time of the day. Failing to engage them with personalized messages means you are missing out on a hot lead.

Other marketers begin personalization first interacting with the audience, but stop short of tailoring messages to the individual throughout the customer journey across devices. For instance, a visitor looked at a t-shirt on your e-commerce site using a smartphone, but he soon left before making any purchase. Later he used a tablet to search for a sweater due to the change of weather. Without knowing this change of behavior, you would continue to send him push notifications about the t-shirt on the phone, rather than the information that meets his real need.

Personalize Campaigns for a Wider Audience Based on Interest

Now, with AI-powered marketing automation tools, marketers can tailor messages on the individual level based on their interests and behavior patterns.

For example, Emma came to your travel site and saw two package deals: one to Tokyo and the other to Bangkok. She clicked on the Tokyo offer and found out the dates were unsuitable. So, she stopped reading and then went on to the Bangkok page where she spent much longer time reading about this destination. Often, this behavior is seen as Emma having equal interests in both locales based purely on the clicks. However, by taking a holistic view, AI is able to identify that she is more likely to go for the Bangkok package. Hence, you can send personalized messages relevant to her real interest.

While learning about your existing customers to delight them is a great step for many companies, you need to make it count – and that means being able to scale campaigns effectively.

Being able to scale campaigns by segmenting the audience based on user interest and behavior is imperative. Not only this way you can personalize content for more individuals who share the same preference, but also target only the people who have shown real interest in a product – perhaps they have checked items multiple times or left something in their cart – rather than just because they have downloaded your app.

An example of poor personalization would be a travel site that sends details of a sale on hotels in Tokyo to all its users, regardless of them all showing an interest in Japan or not. Instead, a more logical approach would be to send details of the various cheap deals to the users who have searched for specific destinations.

An extra step would be to offer deals on car rental or things to do in their destination city. Preferences like this can often get lost in the ether, with prospective customers searching on their phone, tablet and computer and on numerous sites. The average consumer in Asia owns three devices, after all. If this valuable data cannot be tracked, marketers would miss out on a way to improve their strategy.

With the right AI on your side, you can quickly find the signals that people are showing and triggers that will convert them into customers. Many businesses struggle as they grow because they can no longer spend as much time on each customer, but with AI software doing the hard work you can be much more efficient in this pursuit.

Marketing automation can help a business boost its marketing campaign to a certain degree, but without the data and nuances brought about by AI-powered tools, you are often shooting in the dark. Marketing is about getting the right message to the right people, and artificial intelligence is the most efficient way to find out what people want.

Enabling Dynamic Personalization Through an AI-powered Single Customer View

For marketers today, the holy grail is no longer just customer acquisition; rather, they are increasingly focusing on growing the lifetime value of the customer by improving customer engagement and retention. Artificial Intelligence (AI)-powered solutions can help achieve this through hyper-personalization and a seamless user experience across devices.

In an earlier blog, we discussed how personalized marketing could drive better conversion.  For online businesses, personalization forms the backbone of user experience and revenue growth. However, in a survey conducted by eMarketer, 91 percent of decision makers acknowledged that their companies needed to improve their personalization capabilities.

Many enterprises are unable to truly personalize their marketing campaigns simply because they lack the single customer view (SCV) that is essential for personalization success.

The Limitations of Marketing Automation Tools in Developing an SCV

Put very simply, SCV consolidates customer data from your different marketing and customer service channels in one place; thus, offering a complete and comprehensive view of your customer. This, in turn, can help you create better targeted and personalized messages that boost interest, engagement and conversion.

But implementing this is easier said than done. Across the region, companies face a number of challenges when it comes to effective personalization through SCV:

1. As the number of touchpoints grow, with customers browsing, evaluating and purchasing products across devices, companies must communicate with them across devices and channels as well. Often companies lack the technology needed to map the same customer across different devices, and this leads to an inconsistent customer experience.

For instance, a marketer may reach out to the same person with the same message three times on three separate devices, simply because their marketing automation tool did not recognise the customer as one person. In a different scenario, if you send a push notification through a marketing automation tool to remind a shopper of something that she has already purchased, this information would be irrelevant or even annoying.

2. Current marketing automation and data gathering tools (email marketing, google analytics, social listening, etc.) allow companies to access vast amounts of customer data, but with these acting in silos, the data is dispersed across different databases. The result – a fragmented customer view.  

3. Marketing teams are able to gather data about their customers’ behavior and journeys on the website and company app, but lack details about what the same customer do outside the company’s online platforms, leading to an incomplete picture of the customer.

Using AI to Build an SCV for Personalization Success

This is where artificial intelligence solutions can help. An AI-powered proactive marketing automation solution like Appier’s Aiqua, for instance, automatically links your audience across devices. To achieve this, the system requires a massive amount of user behavior data, which comes with Aiqua and a brand might not have in a short time. AI will then find the patterns through the data and link back to a specific type of users and the devices they own. This gives you a consolidated view of each customer’s activity and lets you engage seamlessly with them across devices.

Additionally, it maps their journey inside your platforms with their behavior and interests outside, offering you a comprehensive view of your customer’s complete online behavior.

With this data, you can hyper-personalize your marketing campaigns and engage with users across devices by sending out your messaging at the right moment on the channel or device that is right for each user.

With AI enabling marketers to understand and identify audiences based on interests outside of the company app and website, such solutions become integral to customer discovery as well – allowing you to decipher user preferences before they even engage with your site or app. Using the data consolidated from various channels, marketers can then personalize content for customers who have not even engaged with them as yet, making messaging relevant and specific.

For example, a marketer at a travel company can identify which users are likely to be interested in traveling to France even before they land on the website. They can reach out to these prospects with personalized messaging meant to arouse interest and also proactively set rules to personalize the content of the website on the prospect’s first visit.

AI-powered SCV hence allows you to hyper-personalize marketing and offer customers products that they are actually interested in, thus shortening the purchase cycle and driving conversion. Use SCV as a foundational platform for your cross-channel marketing efforts and leverage the insights derived from the data to target the right customer at the right time on the right channel.

Making 1:1 Personalization Possible With Artificial Intelligence

The way a company markets itself and its products or services can have a huge impact on its profits, brand strength and longevity. While a poorly planned and executed marketing campaign is unlikely to help a company greatly, using modern techniques such as personalization powered by artificial intelligence (AI) can push your campaigns to the next level.

Marketing Personalization Is A Necessity

While many brands have already started to personalize their messages using marketing automation tools, online marketing allows for much more specific targeting, almost on an individual basis. Potential customers leave breadcrumbs of their interests across the internet, through social media, shopping sites and search engines. This data can help you craft a better marketing campaign, one with tangible benefits.

Personalization at scale can lift revenue by 5 to 15 percent for companies in the retail, travel, entertainment, telecom and financial services sectors, according to McKinsey & Company.

There is no surprise to see that personalization is becoming a major consideration as McKinsey highlighted that more than 90 percent of retailers believe this is a top priority. However, only 15 percent of these companies are actually doing a good job at it.

Challenges With Marketing Automation Tools Today

One of the most important aspects of marketing is making sure you get your message to the right people. The more specific you can be with your target audience, the more likely you are to see a positive return on investment in your campaigns. There is little point telling a vegetarian about your new steakhouse, or advertising a luxury resort to backpackers.

A major limitation of many marketing automation tools today is the lack of available data. Whether it is because you are looking at a small data pool or that you cannot track a user over multiple devices, having holes in your data can make your personalization less accurate and therefore less effective.

For example, a user may access your site on their computer, phone and tablet. Many personalization tools don’t have the capacity to see this as one user and will instead report three different people looking at your site. This gives a disjointed view of the user and means you miss out on valuable information about the buyer’s journey.

Marketing automation tools do not always understand human actions or emotions either. They could fail to recognize that after someone has made a purchase, he or she will no longer want to buy the same item. This can often come down to a lack of data about a user’s behavior.

Another challenge businesses have is that they find it difficult to scale their marketing efforts and manage engagement across all their channels. One cause for this is the number of different tools they need to cover all the bases, and upgrading each of these can be a costly or impractical exercise. With different tools in place, there is often a lack of communication between what marketers are seeing, making it hard for them to act quickly and efficiently.

How Can AI Improve Personalized Marketing?

There are many ways that AI techniques can help brands improve their marketing campaigns. This is particularly true in terms of zooming in on one particular type of customers and scaling up for large projects.

Without any sort of AI, the information companies know about a visitor when they visit a website can be limited. However, the visitor may already have shown information about the type of person they are and what sort of product they are looking for. For instance, a consumer often purchases fashion goods from an ecommerce site A, but she also buys baby products from site B. Having this insight available for site A means the visitor can be exposed to relevant products and information to keep them engaged further.

AI can also help you engage potential customers once they leave your site. For instance, someone who has abandoned a cart on your site can receive a reminder about the product that they have left waiting, perhaps with personalized suggestions for other items if that one wasn’t quite right.

Another scenario could be knowing whom to send certain newsletters to. You may have a sale or promotion on products that might be of interest to some of your contacts. Sending one email campaign out to all your subscribers isn’t necessarily the best approach. So, knowing who has shown an interest and who would be likely to buy that product can help make that email marketing campaign more effective.

AI-powered personalized marketing is proving to be one of the most effective ways to maximize a marketing budget and it’s something that brands are increasingly making use of today.

Is Artificial Intelligence Breathing New Life Into Email Marketing?

As digital channels such as social media continue to be a vital tool for customer engagement and product promotion, it’s easy to overlook “old school” tools like email. However, recent improvements in email marketing – underpinned by artificial intelligence (AI) – are turning email marketing into a viable marketing tool.

Compared to the possible instant response on social channels, email marketing tends to be less effective due to its limitations, including difficulty in finding and retaining subscribers, and low open and click-through rates.

Conventional wisdom would have you change certain things about your email content to improve its performance, such as offering more discounts, crafting a better subject line, or sending messages with a different frequency. But these suggestions are based on the notion that, as a human, you can guess why readers are or aren’t connecting with your content. While true to a certain extent, this assumption requires a high degree of trial and error to arrive at the desired response from recipients.  

Now, help from AI makes it possible for businesses to discover new lookalike customers, better understand and segment existing customers, predict topics of interest, and anticipate customer behaviors. These actions can help you solve some of the most vexing challenges with email marketing.

Increase Open Rates With AI-Powered Segmentation

There is a reason why your readers aren’t connecting to your content. By taking an AI-based approach, you can see a highly accurate analysis of the problem – as well as your audience’s needs – putting you considerably further along than if you only employ guesswork.

While only 21 percent of marketers in Asia Pacific delivered personalized email beyond just name in 2017, 76 percent of them indicated that they were keen to do better personalization in email marketing, according to a Econsultancy report.

The report also pointed out that using a data point in addition to the recipient’s name is twice as likely to trigger them to open the email. Imagining if AI could write a short novel that almost won a literary award, it can also analyze all the user data including the content consumed by users across screens, and then extract the most frequently used keywords to identify topics that your audience is most interested in, and create predictive segmentations.

Once you gain such actionable insights, you can then develop content or create offers that correspond closely with their preferences and needs. As AI is capable of identifying as many keywords as possible, you will have multiple touchpoints to engage with your audience.

You can even predict who will respond to your new campaign based on their responses to past campaigns, and customize mailing features that make it easier for them to do so.

For instance, a major online and print publisher in Taiwan used to send the same emails to all readers, resulting in low open and click-through rates. Content and headlines weren’t relevant or sufficiently attractive to trigger recipients’ interest.

By adopting an AI-based approach, the publisher used deep learning to link reader profiles with their online behaviors to establish segmented profiles based on key attributes, such as age and interests. This process allowed the publisher to tailor mailing lists to the right group with appropriate marketing content. As a result, its open rates increased by 42 percent, and click-through rates increased by as much as 107 percent.

Grow Your User Base With Lookalike Audiences

The right AI models can also analyze data gathered from users’ online activity to find those who “look like” your current customers, helping you develop targeted ads and other outreach efforts. This process starts with the breakdown of demographic data about your current customers with as much granularity as you choose. It can include data from your website, campaigns, apps, customer relationship management software, application programming interface integration, and more.

An AI-enabled platform then maps that information with additional sources to find close potential customer matches. Using this valuable data set, email outreach becomes less of a guessing game and more of a precise targeting tool.

Retain Subscribers with AI Prediction

Based on behavior patterns, the AI-enabled platform can help you identify subscribers who are likely to leave your service. Certain actions indicate their readiness to move on, but you can prevent this migration if you give them reasons to stay. Once you have identified this subset of your subscribers, you can plan and implement your re-engagement strategies, such as:

  • Creating emails targeted solely to this group of “potential unsubscribers”, and segmenting further into interest groups.
  • Offering surprises, deals or rewards specific to those groups.
  • Using formatting and links to make it easy for readers to take action.

AI is the most promising tool that is driving personalization in email marketing like never before. The AI-based approach makes it possible to identify the behaviors and interests that should trigger customer engagement in email marketing, and determine how the content delivered should be customized to produce the desired outcome. The benefits mentioned above are testament to how AI can make this old marketing method thrive again.