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.

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.