In 2017, online gift retailer RedBallon’s marketing team started working with “Albert”, a digital marketing platform powered by artificial intelligence (AI). Working across Facebook, Google, YouTube and other paid and earned media channels, Albert autonomously targets audiences, mixes and matches creative assets, buys media, runs campaigns, measures performance, applies insights from one channel to another, and then makes adjustments based on what “he” learns to optimize the return on marketing investment. With Albert’s help, the total cost of customer acquisition across channels for RedBalloon was reduced by 25% in less than one month. He also relieved the marketing team of many of the manual and process-driven tasks they’d been doing. The time they were spending manually executing search campaigns, researching keywords, or altering social media audiences was redirected to more strategic activities, such as devising campaigns that targeted niche, high value, and previously ignored audiences uncovered by Albert. The AI was finding new audiences that the company had never even considered, debunking many of the long-held beliefs RedBalloon had about their audiences and the effectiveness of their campaigns.
When Naomi Simson founded RedBalloon, an online gift retailer that sells personal experiences, she was pioneering the category in Australia. With a $25,000 personal investment and a small office in her home, she began aggregating sales leads and aggressively acquiring customers through very traditional marketing means — like yellow page advertisements. It was 2001, and online advertising was at its nascent stage. Internet Explorer was the leading Internet browser and Google AdWords had only just recently launched. With a cost of customer acquisition of just 5 cents, Simson’s traditional approach to advertising was generating an impressive return on investment. RedBalloon was setting the pace for gifting experiences like outdoor adventures, wine tastings, concert tickets, and spa treatments.
By 2015, RedBalloon was delivering more than four million customers to businesses across Australia and New Zealand that offered “experiences.” Simson wasn’t overconfident, but at this point, she felt like she knew every audience for experiential gifts that existed in the market, along with the most efficient ways to reach them.
Fast forward to 2016, and almost all of RedBalloon’s brand advertising was invested in traditional media outlets like radio, print, billboards, and pop-up retail stores. The company’s cost of new customer acquisition had ballooned from 5 cents to $50. Despite the fact that the company enjoyed massive brand awareness, escalating acquisition costs were destroying margins. Furthermore, the traditional audience for experiential gifts was no longer connecting emotionally with the RedBalloon brand. The marketing team was getting lost in attribution, pulling the same search engine marketing levers, talking to the same audiences, and creating the same campaigns with diminishing returns. The situation was untenable. Simson knew that the company had to transform marketing to find previously unexplored audiences and to make media buying decisions more autonomous and efficient.
Enter “Albert”, a digital marketing platform powered by artificial intelligence (AI). Working across Facebook, Google, YouTube and other paid and earned media channels, Albert autonomously targets audiences, mixes and matches creative assets, buys media, runs campaigns, measures performance, applies insights from one channel to another, and then makes adjustments based on what “he” learns to optimize the return on marketing investment. I met the team at Albert (formerly known as Adgorithms) while I was doing research into artificial intelligence, machine learning, and data-driven marketing technologies for my book, Marketing, Interrupted. As part of my research, I interviewed several of Albert’s customers, including Simson.
In 2017, Simson and her marketing team put Albert to work immediately, processing the company’s large database of customer interactions and transaction history. After digesting all of this data, Albert identified and bought more than 6,400 keywords to improve performance across RedBalloon campaigns in the first 24 hours of operation. Most marketers use last year’s attribution models as a baseline to inform decisions for this year’s media buys. Not Albert. He retests in real-time to try and disprove existing models and find a different and more efficient way to reach the target. With Albert’s help, the total cost of acquisition across channels for RedBalloon was reduced by 25% in less than one month. He also relieved the marketing team of many of the manual and process-driven tasks they’d been doing. The time they were spending manually executing search campaigns, researching keywords, or altering social media audiences was redirected to more strategic activities, such as devising campaigns that targeted niche, high value, and previously ignored audiences uncovered by Albert.
Despite Simson’s conviction that she knew every buying audience in Australia and New Zealand, Albert was finding new audiences that the company had never even considered. For example, Albert identified an audience cluster of “men over 65 years old in Melbourne who love to skydive.” Albert also revealed pockets of ex-pat communities in the United States and Europe who wanted to buy experiential gifts for their friends and families back home, but were unaware of RedBalloon.
Albert identified these new high-value audiences by trying thousands of text-image combinations on small “micro-segments,” observing which audiences responded along with the specific combinations that triggered their response. Once he identified the highest-performing micro-segments, he scaled his efforts to larger audiences and served them hyper-personalized messages based on what worked with the smaller groups.
Albert acts on these types of insights as he goes, rather than stopping to ask for approval, which can present a learning curve to new adopters of AI, but he also shares what he’s learning along the way. Using large, rapid scale, multi-variant testing, Albert confirmed his initial learnings and insights and expanded upon them, all while autonomously analyzing and revising his decisions based on changing customer behaviors and patterns over time.
Albert debunked many of the long-held beliefs RedBalloon had about their audiences and the effectiveness of their campaigns. Previously, RedBalloon had only been engaging with about 1% of their reachable base on social media and those campaigns focused primarily on driving conversion at the bottom of the sales funnel. Albert started running campaigns to engage the other 99% of the reachable audience. By not just focusing on “closing the deal,” Albert increased brand relevance and consideration, nurtured the audience, and importantly, plugged leaks in the top and middle of the funnel. As a result, the conversion rate from Facebook campaigns managed by Albert increased by 750% in Albert’s first year of operation.
Albert’s results have been so impressive to date that Simson is now encouraging RedBalloon’s CFO to think in a very different way about the marketing budget. In fact, she’s challenging the notion of a “budget” altogether. Albert is now generating $15 of return for every $1 of marketing investment. If you have a finite, bounded marketing budget, that implies that you must stop investing when the budget is exhausted. But if you can get a 15x return, why would you stop? Simson’s argument is that the brand should continue to invest until it sees diminishing returns on that investment. Whether or not she wins that argument, you can bet that Albert will have a bigger slice of the RedBalloon marketing budget to work with going forward.
The adoption of AI in the marketing department will only continue to increase as businesses enjoy the benefits of real-time segmentation of customers, personalized messaging, predictable customer value, and optimized media buys. By eliminating the tedious manual tasks of tweaking business rules each time new customer information is captured, AI will liberate marketers to focus on more strategic and creative activities like campaign planning. Without AI, it will be too difficult for a marketer to compile and process the huge amounts of data coming from multiple sources like website visits, mobile app interactions, purchase transactions, and product reviews. Those who are slow to adopt AI will find themselves at a competitive disadvantage because they won’t be able to make timely, accurate, and profitable predictions about their customers.
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