Gain Quality Leads That Won’t Break Your Budget With Artificial Intelligence

Cost per lead (CPL) has long been considered the gold standard in marketing – it’s hardly surprising, as 63 percent of businesses cite generating traffic and leads as their biggest marketing challenge.

However, while CPL can be a reliable metric, it does have one rather large omission: it doesn’t consider the quality of the leads. A low CPL is desirable, but it shouldn’t come at the cost of high-quality leads – this will result in a low conversion rate, and fewer sales for the brand. No one wants that.

The good news is that a low CPL doesn’t have to mean low-quality leads. By harnessing the power of artificial intelligence (AI), marketers can find high-quality leads with a high conversion rate, and at the same time bring down the CPL.

Pick Out the High Performers: Identifying and Targeting Lookalike Audiences

An AI-enabled platform can identify which devices customers use, and build a behavior profile based on their cross-screen activities. Once you know who your highest performing audience groups are (i.e. those most likely to convert browsing into purchases) by demographics and interests, the platform can identify other users who share those attributes. This is called finding lookalike audiences.

Brands can therefore identify and buy access to the best audience for their campaigns, expanding their reach beyond the traditional domain.

Maybe your best audience is the one who viewed 10 products over the course of three days, as opposed to those that viewed five products in a single day, for example. The traditional marketing approach would be to target each of these groups in turn and hope for the best. However, AI removes the guesswork by allowing you to focus on those highest performing customers for maximum return.

Remarketing to reduce delays in sales

Artificial intelligence also helps with remarketing (reaching potential customers who have expressed interest in a product but not yet converted). By reaching the user on every screen they use, you will shorten the time between the initial visit and the actual purchase.

For example, if a user browses a product on his laptop and later on his smartphone, an advanced system can remarket to him via both platforms, through email for the laptop and by an app notification for the smartphone, say. This makes it much easier for the consumer to purchase, as it only involves a couple of clicks, rather than them switching devices and/or from an email program to a web browser.

A Person, Not a Device: The Importance of a Single Customer View

An AI-enabled platform lets you tailor recommendations and advertising creative to each user’s unique cross-screen behavior and browsing history (aka the Single Customer View). Because it recognizes these activities as those of an individual, and not just a device, it builds a picture of them as a person, with certain interests, behaviors and habits. Not only does this increase the chances of a higher conversion rate, it also makes it easier to find lookalike audiences, because you know more specifically what you are looking for.

For instance, you are interested in the cross-screen web browsing history of a male consumer named A. Using traditional marketing techniques, you would only see that content being consumed on different screens is about sports, technology, finance and travel. Multiple touchpoints make it hard to tell how many consumers are using these devices, and these topics are also too vague to really build a picture of what he is interested in.

By analyzing the cross-screen behaviors and the keywords within the online content A consumes, AI can link all the devices owned by him, and determine that he is searching for basketball with virtual reality, bitcoin, budget bed and breakfasts while travelling, and so on. Immediately you have a much more vivid picture of who A is and where his interests lie, which enables you to tailor your marketing materials to him as an individual. Crucially, you can start a dialogue with A – and with those who share his interests – which will build a relationship between him and your brand.

Put a Limit on It: Frequency Capping and the Power of Saying No

Of course, with all this power at your fingertips, it’s tempting to bombard the consumer with marketing messages, but that risks overloading them, which will only serve to alienate them from your campaign. It will also cost you more.

Instead, smart AI algorithms employ frequency capping to ensure you don’t overwhelm your customers. It also means you spend your budget efficiently and limit wasted impressions. As it works across every screen your user owns, it knows they are the same person instead of assuming a new individual for each device. That way, you won’t send them mixed marketing messages.

Capping is available per day or per action during the life cycle of a campaign. AI can find the best rule depending on your preferences. You can also limit it to a total number of impressions or clicks.

Taking global beauty and skincare brand Estée Lauder as an example, it employed the above techniques to huge success. It used Appier’s CrossX Lookalike feature to identify new, high-value, young audiences from the profiles in the CrossX database with data collected from over 3,000 campaigns run by Appier. Estée Lauder increased its number of leads by 167 percent, while reducing its CPL by 63 percent. It also shortened the time to conversion among valuable users who were interested in the brand by using CrossX’s remarketing and frequency capping tools.

AI is an immensely powerful tool for marketers looking to increase the quality of their leads, while decreasing their cost per lead. It shows that when it comes to marketing leads, low cost can mean high quality.

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.

 

3 Steps to Make Sense of Your Data for Lead Generation

There is more data available than ever before. The explosion in data volume could help marketers do their jobs better. However, in a lot of cases, it creates confusion, as marketers are swamped by the sheer volume, and find it hard to sort the useful data from the useless.

Thankfully, help is at hand. In this article, we will show you three simple steps to make sense of your data, in order to make it work for you and generate leads that can help expand your business. Think of it as a life raft to help you stay afloat in an ocean of data.

Step 1: Streamline the Data

This step involves bringing together all the data gathered with various methods from different sources all under one roof. This can include data from your official website, campaigns, apps, CRM, API integration and more.

With data from such disparate sources, it can be confusing to extract any meaningful insights. By integrating fragmented digital data and unifying different data sets with the right tool, you will be able to get a comprehensive view of a user, addressing one of marketers’ most common pain points.

This step will also allow you to focus on a specific business goal. Maybe the data shows your customer churn rate is too high and you want to bring it down. Or that you would like to expand your company’s reach into new customers and new markets. Providing the data is accurate, it should provide a realistic snapshot of your company’s health, and help you gain actionable insights to achieve your business goals.

Step 2: Data Segmentation Based on AI Prediction

Your data is all collated and streamlined, and you know which areas you would like to focus on, such as more registrations for membership or subscriptions to your newsletter. Now how do you go about achieving those goals? Thankfully, artificial intelligence (AI)-powered systems can create AI models to predict customer behavior, and all without hiring a team of in-house data scientists.

As the customer journey increasingly involves multiple screens, it becomes harder for a human brain to make sense of all the data from customers’ cross-screen conversion paths, and segment users by multiple dimensions. However, AI systems can work on the multiple dimensions to create AI prediction models, forecasting variables like conversions and churn rates based on the segmented data. For instance, by understanding previous campaigns’ impact on your business, you will be better placed to formulate a future strategy.

CommonWealth Magazine, Taiwan’s most influential economic news media, leveraged Appier’s Aixon platform to combine data from different sources to create a unified customer view across screens. Based on this unified user view, it was able to generate new audiences, improving subscriptions and increasing online sales.

In fact, for every dollar CommonWealth spent on reaching audiences identified by Aixon, it generated 12.2X worth of revenue. The campaigns exceeded its return on ad spend targets by 300 percent, while subscriptions and purchases increased by 404 percent.

Step 3: Lead-Generation Campaigns Based on AI Insights

Once you have these AI predictions at your disposal, you are ready to deploy your new campaigns in order to convert on your business goals.

More advanced systems can deliver adverts via multiple marketing channels at once. This will increase the chance of you reaching your users in meaningful ways, as it helps you ‘talk their language’. For instance, you can reach the target audience Andy on Facebook through a relevant banner ad with minimal text, and deliver a dynamic product ad when he visits an e-commerce site on a PC.

If you approach your customers in the wrong way, you will dissuade them from associating themselves with your brand – they will see it as something ‘not for them’, but for someone of a different age, outlook or with different interests.

As well as speaking to them in terms they understand, you can optimize each advert and campaign specific to the platform you are using in order to better engage your users.

For example, luxury automobile manufacturer Audi tapped AI technology to drive test drive leads across screens, delivering a cross-screen conversion rate between 23 and 48 percent higher than to a single screen.

Making the data work for you

Data isn’t the problem – chances are, you have the correct actionable data at your disposal right now, but only by using the correct system can you gain valuable insights that will help your business, and bring the useful data from arm’s length to being right at your fingertips.