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ChatGPT, Dall-E… AI is making a lot of global noise, especially taking over the advertising and marketing industry with great hopes of making it better. At Albert, we believe that AI isn’t about fully replacing us humans. Instead, it’s about empowering marketers with tools that help with some of our tasks, and free us to focus on business driving strategies, that take our efforts to the next level. 

Albert was developed based on the notion that you can simply get much more done and see immediate results in less time than you could expect. It’s the AI platform that combines marketing departments, plans advertising strategies in advance, executes campaigns, and optimizes along the way. 

To provide an idea of what’s possible when advertises join forces with AI, we decided to pull the curtains for a behind the scenes look at our customers’ campaigns. Check out these 4 case studies: 

1) A Retail Brand Increased Return on Ad Spend by 30% with Better Efficiency and Insights 

Challenge: Carbtree & Evelyn has been pampering customers with home spa products and fragrances, among others, since 1972 in over 200 stores across 65 countries. Its advertisers managed campaigns manually and kept reaching the same audience. The company wanted to reach new audiences, yet lacked necessary insights. 

Solution: Albert gained data from all previous media campaigns initiated by the brand understood what’s working via multivariate testing, and only then, cautiously, used the company’s budget to run new and smarter campaigns on social and search platforms 

Results: The company welcomed new personas data and, with Albert’s insights, understands its customer journey better. That contributes to both branding and product development. Return on ad spend quickly increased by 30% – without increasing media spend. 

Read the full case study here. 

2) A CPG Brand Gains a 20% Revenue Increase during the Most Competitive Time of Year… in Previously Considered Lackluster Geographies 

Challenge: A high growth CPG brand, with thousands of products, needed to grow its margins for established distribution channels as well as its developing ecommerce presence. It needed to do so in a crowded market. Moreover, it decided to let go of its agency and needed in-house help. 

Solution: Around Black Friday, the country was split between the agency and Albert, the latter getting less valuable territories. Albert combined previously connected campaigns into one prospecting machine,and discovered profitable customer micro-segments. It autonomously, strategically shifted budgets between channels. The scale it reached was more than a human could do. 

Results: At the most competitive time of the year, in geographies the brand discounted, Albert generated a 20% revenue increase for the brand. 

Read the full case study here. 

3) FMCG/CPG Company Reduces 72% of Costs After Quickly Testing 11,340 Options 

Challenge: A global snack food company wanted to increase registrations for its loyalty program. 

Solution: Using all the historical data, Albert targeted the most obvious customers and reduced the cost per lead from $10.75 to less than $3 – within a week. Then, it started testing other audiences and gave them more signup options. It created 30 ad sets, tested them out, paused the low performing 15 creative assets, and autonomously shifted the budget to high performers. Then, the company was able to produce more accurate new assets. Albert used them to create 30 more ad sets. 

Results: After quickly testing 11,340 variations in strategies, channels and audiences, Albert had 35 ad sets it created, which, together, delivered 87% of the budget. The added bonus? The company discovered their audience doesn’t respond well to the character-focused messaging it had been using. Instead, their audience prefers promotions while getting shown a range of options. 

Read the full case study here. 

4) Global Insurance Firm Increases ROAS by 130% Within 30 Days, 200% Within a Month 

Challenge: Siloed marketing efforts and lack of data kept a global agency from scaling. 

Solution: Albert took over the company’s advertising. It discovered new insights, such as when there was a need for more visuals, as well as new audience segments – all within a week. 

Results: The goal of 130% return on advertising spend was met within 3 days. 200% within a month. 227% year over year conversion increase. 

Read the full case study here. 

Skyrocket Your Campaign, Too 

When advertisers work with Albert, you give it your KPIs and creative assets. And access to your data, of course. Albert takes over all the time consuming stuff – planning your strategy, executing your campaigns, restructuring creative assets in a large variety of combinations, optimizing audience targeting and budget allocation… you name it. It has over 200 skills. 

That said, Albert is, of course, a software. A very smart AI software, but still not a human being. Therefore, anyone who works with Albert also gets an account manager and a campaign monitor, who verify Albert doesn’t make some embarrassing mistakes. Advertisers get lots of automation without giving up campaign control. 

Make your next campaign (and the one after that) a success story. Check out Albert here. 

An interview with Sagi Weinberg, Sales Director at Albert

We completely understand why people fear the recent uprising technology. “As ChatGPT, MidJourney and other AI tools gain popularity, people hear about their phenomenal capabilities, yet aren’t familiar with these technologies. Therefore, they tend to think that, just like AI-based robots have replaced employees in large logistical facilities, they’ll replace content writers, programmers, designers and marketers,” says Sagi Weinberg, Albert’s Sales Director. Sagi, a long-time digital marketer with background in Sales, has vast experience in leading brands to great success. Sagi is highly experienced in planning and executing holistic marketing strategies aimed to drive measurable and sustainable bottom line results by identifying the business’ structure and needs, considering online and backend flows, creating a healthy marketing mix, devising a full funnel, channel-customized approach and implementing the right technologies.

With the latest talk about AI, many online publications are capitalizing on this trend, as amplifying fears means amplifying clicks. Before we know it, a range of professions seems to be on the edge of extinction. But for marketers, at least, it’s not the end of the story. As the following interview clarifies, AI won’t replace marketers. 

Why AI Makes Marketers More Valuable 

It’s true, Sagi says – “humans have inherited limitations. They take vacations, take weekends off, get sick and need to sleep. A machine doesn’t. It also doesn’t tire or get confused by processing amounts of data humans simply aren’t able to.” So again, marketers’ fears are understandable. But “that’s exactly where humans can capitalize and use machines to enhance their capabilities,” Sagi says. 

Set the Foundation for More Efficient Campaigns 

“AI helps you connect the dots between online and offline marketing efforts,” and between top and bottom of the funnel, Sagi says. “It closes the loop on the whole funnel,” he says. 

Therefore, he explains, marketers can focus on a coherent, unified strategy that leads to better growth, more efficiently. 

Simplify and Deepen Market Research 

… and do so at a greater speed, Sagi says. AI can find low hanging fruit audiences that us humans never would have considered, like Americans buying gifts for an Australian holiday because they have loved ones in Oz. It can also let you know how to communicate better with your existing, but lower performing audiences. 

Test A Wide Range of Creative Assets 

There’s only so much campaign managers can do manually on a daily or weekly basis, but there’s no limit for what AI can do. In our platform, Albert, for example, you can automatically test a wide range of copy-visual combinations to quickly find the best fit for each audience segment. It actually does it for you, without the need to set anything up. With one time setting and uploading of assets, Albert creates new creative sets for either search or social platforms, knowing the limitation of each platform (creative wise). 

Free Up Your Creativity 

Even though AI takes the mixing and matching of creative assets, humans are still the ones creating the assets. In addition, according to Sagi, when AI does the heavy lifting on time consuming activities, such as massive testing and data analysis, marketers have more availability to delve into and express their creativity – not just in copy or design, but in strategy, too. 

As Joe Hart, president and CEO at Dale Carnegie & Associates, reports, “creative companies are 1.5 times more likely to command a greater market share” and 67% of “the most creative companies… had above-average organic revenue growth.” Meaning, AI won’t replace marketers because companies need the marketers that combine forces with AI tools. 

Make the Most of Your Budget 

Sagi says that, with AI, “you can manage budgets in an unbiased, efficient manner. AI tools don’t have a platform preference. They can look at your whole activity from a bird’s eye view, and automatically shift budgets within the channel and across channels, toward the best performing activities.” 

Optimize 24/7 

“Campaign managers, and CMOs use tools like Albert to perform optimizations 24/7, even when they sleep,” Sagi says. “AI can analyze huge volumes of data at any given moment. Tools like Albert are capable of simultaneously analyzing stats of multiple ads, across multiple campaigns in various platforms, and across different channels,” he says. 

“Plus, rather than looking at last month’s best performing ad, keyword or audience, which us humans usually do, AI can do it live, while also exploring new audiences,” he says. “It uses one set of logics that make all the decisions unified and persistent, without compromising KPIs,” he says. 

And it keeps you in the loop. Albert, for example, “plugs into your ad account, manages the activity and later shows the number of calculations that were made, the amount of actions that were taken, the best performing ad variations and geographies. It breaks down the most relevant audiences and provides in-depth insight on every step of the marketing funnel in every channel respectively, as well as the whole paid media activity holistically, to help marketers make the right decisions in terms of brand-level creatives, localizing creatives for specific markets, and all the way down to adding keywords they could never have discovered otherwise to a landing page,” he says. 

Before AI, “humans could only dream of such efficiency,” he says. 

How AI Helps Marketers Prove Their Value to the C-Suite 

As a late 2022 LinkedIn and YouGov survey revealed, “77% of CMOs globally feel under pressure to prove greater short-term ROI on their marketing campaigns.” 

Sagi agrees. He thinks that, not only AI won’t replace marketers – but it will also help them keep their jobs and thrive professionally. “A clear view of results is essential for decision makers,” he says. Thankfully, “there are many ways to test the efficiencies of humans vs. machines. Efficiencies can be measured on many levels, including saved time, growth and other success metric improvement,” he says. 

You can even measure the machine’s success directly vs. your best PPC marketers. But be aware – every time we did this here at Albert, the machine won. So be prepared to share that alongside the achievements your human team accomplished thanks to more time, better data processing and deeper audience targeting. 

AI Won’t Replace Marketers Because AI Needs Marketers to Succeed 

According to Sagi’s insights, today’s popular AI tools are great for amplifying marketing, but marketing management still requires the human element. Marketers are still needed – and will be needed for a while – to develop and manage the vision, goals and business model. They need to decide how they measure KPIs, and take all the above into account, in addition to the company’s limitations, when reviewing actionable analytics and deciding on next steps, he explains. 

Therefore, it’s marketers who “decide on appropriate budgets, determine dates for time-sensitive or seasonality related promotions, etc. Those are strategy level decisions humans will always be necessary for,” he adds. 

And there’s more. Marketers are the ones who understand their brands best – on top of industry regulation, sensitivities and brand safety. “They need to make sure they adhere to those requirements,” he clarifies. 

“This is how Albert was designed,” he says, inviting you to get in touch for a free demo with his team. “It was designed to work hand-in-hand with humans. Humans are the ones who set the guardrails, define guidelines, and have a confined framework configured to the AI to work within,” he says. “It’s your brand, and you’re still its leader.”

With ad creative optimization subject to user biases, like preferences for bold headlines, images, and colors, etc., Zoomd-owned Albert AI technology enables true creative optimization driven by real-time creative performance across products, ads, campaigns, and market segments.

One of the last areas of marketing to benefit from AI-driven optimization is ad creative.

The actual creation of ads will probably be the last area of marketing to benefit from AI-driven technology, even with the recent breakthrough of technologies like Chat GPT-4.

But the optimization of ad creative is very well-suited for AI technology today because of the subjectivity people apply when optimizing ads. While it’s easy to compare the performance of two distinctly different ads, optimizing creative performance to determine the optimal size and color of the font for the ad’s headline and other subjective creative elements is difficult for people because of our inherent biases.

“A creative director who has succeeded with bold headlines or has a preference for certain colors and color combinations will bring these biases to the ad creation and optimization process,” said Nir Huberman, VP Product at Albert AI, part of the Zoomd marketing and publisher platform. “But Albert is more methodical, breaking down each potential parameter that impacts performance, testing each one by one. That’s why Albert’s technology can improve creative performance by optimizing ad parameters from among the options provided which enables exceeding client KPIs. Albert also provides a lot of value for marketers by knowing when to refresh or replace an ad’s creative.”

And by determining which ad creative performed best using Albert, marketers are in a better position to create new ads that will perform.

An e-commerce company contracted to work with Albert AI with the stated KPI of increasing Return On Ad Spend (ROAS) by 500%, a KPI that Albert’s team believed was realistic. A few months after the conclusion of the onboarding process, Albert achieved an 800% improvement in ROAS. And in subsequent years, this e-commerce company, now in its fourth year working with Albert, is still achieving improvements in ROAS that are between 10-20%.

For this e-commerce company, Albert was able to optimize ad creative by creating the best-performing ads for each target segment and each ad platform/channel. Albert’s technology creates the optimal ad by selecting the best images, colors, fonts, and texts that will generate the most cost-effective performance for the target audience. Finally, Albert’s technology was able to efficiently determine when to refresh and then change ads to ensure optimal ROAS.

Albert is an advertiser and an agency’s autonomous marketing ally. The technology leverages AI to create ads that optimize campaign performance, from keyword, audience, platform, and device selection and bidding to creative optimization across search, social, display, and cross-channel. Albert assists marketers and agencies – from defining campaign strategies and messaging to the creation and optimization of ads across audience segments and platforms. By working 24/7 to continuously optimize campaign performance, Albert AI complements marketer and agency teams, giving them the insights to make them smarter as well as more efficient and effective.

We’ve been hearing about robots taking over humans’ jobs for decades in almost every professional specialty imaginable, including industrial factories, the legal industry and, of course, advertising. 

Yet here at Albert, we believe in human-machine collaboration (AKA advertising technology). There are some tasks that only humans can do, so outsourcing the rest to machines helps us do them better. But what makes a great collaboration? You know, the kind that generates significant results, that make advertisers the new stars of their companies? 

To find out, we talked to our very own Product Solutions Manager, Nir Huberman. Nir has been in the industry for about a decade and a half. At Albert alone, he spent the past 12 years climbing his way up from head of optimization to head of product and, then, to VP of product solutions, so he has tons of behind the scenes knowledge. Here are his top requirements for machine-advertiser collaborations that will increase your bottom line in 2023. 

1) Create a Holistic, Omnichannel Marketing Operation 

If your marketing departments work in silos, you’re not alone. Too often, companies separate teams per channels, platforms or strategies. They have different departments for Google, TikTok, direct marketing, digital marketing – you name it. It’s understandable, as every part of marketing requires its own specialization. But no channel or platform exists on its own. 

What you do on one platform impacts how customers experience your brand elsewhere, online or off. Just as importantly, the data you generate on one platform can help you optimize results everywhere else you operate. 

Therefore, after working with leading brands from across the world, Nir suggests unifying your entire marketing operations. This is especially useful when working with machines. You already have a machine that can process lots of data, plan and execute a complex strategy… You might as well make the most of it and let it optimize your entire marketing results across channels. 

2) Combine Paid with Organic 

Nir recommends taking your holistic marketing collaboration even further by combining paid with organic into one plan. 

“As a strategic business, you want to use your paid efforts to empower your organic efforts – brand awareness, direct communications, loyalty programs, email, etc,” he says. “When you strengthen your customer base, you create a business that’s objectively healthier,” he explains. 

3) Plan Way Ahead 

“If I give my machine a $100,000 budget in November and don’t tell it there’s this thing called Black Friday, it’ll likely blow the entire budget before Black Friday. The same goes for annual planning,” Nir says. 

“Look ahead at your entire year. This is my budget, these are my KPIs, these are my strategic dates, milestones and promotions across the year. Strategize on an annual level, and your advertising machine will work much more efficiently,” he says.  

4) Set Undisputed Success Metrics 

The most critical part of collaborating with machines, according to Nir, is getting clear on your KPIs (key performance indicators or success metrics). Often, we want… 

=> Leads, but also to… 

=> Limit how much we pay per click, but also to… 

=> Determine our lead to sale conversion rate, but also to… 

=> Use multiple tools to measure the same metrics, but also… 

… it’s a sure way to set ourselves to fail, or at the very least, leave ourselves without an accurate measurement we can use to strategically predict future success. 

“Understanding what’s actually essential for the business and being specific are prerequisites,” says Nir. “When I tell a machine to rely on Google Analytics, it pulls all the data and studies the process there. If I change things a week later, I lose everything the machine has learned and need to start training it from scratch,” he says. 

5) Conduct Ongoing Monitoring 

Another key requirement when choosing and working with AdTech is your ability to monitor its activity and impact how it will move forward. “Don’t just set it and forget it, or come back a month later,” Nir says. 

Sure, your advertising machine relieves a lot of your previous duties, but your help is still needed. “Look at how your campaign is going at a high level, and if something looks off, talk about it with your account manager or make changes in the software. Maybe you need a specific integration, for example. Either way, without your feedback, it’s hard for the machine or its providers to help you, because there are things only you and your team know,” Nir says. 

6) Choose Great Tools 

Nir stretches the significance of choosing tools that actually support your goals. Once you figure out your long term and short term KPIs – remember to be specific and consistent – make a list of everything you want to accomplish with the type of tool you’re looking to add to your toolbox. 

“There are many tools that help you run campaigns. Usually, they recommend what’s best to do, or you set a test and use the tool to better understand your audience. We built Albert to both plan and execute campaigns. Among others, it builds a budget, manages your creative assets, stops what doesn’t work, continues what does, and so much more,” he says. You need to understand what’s missing from your current arsenal of team members and software products, and only then go out and get it. 

7) Trust the Process 

“Think about autonomous cars. There are many driving aids, but there isn’t a car where you get in, tell it to take you to the office, and that’s it. You still have control over the car. You can still make changes. But you need to trust the car to take you where you need to go. Yet people are scared. And it’s hard for them to let go of control in campaigns too. For some, there’s a big fear to let go of a large media budget. For others, they think they can drive the campaign better than other humans or machines,” Nir says. 

“We see this with Albert. Sometimes, people don’t give it enough creative materials to allow it to efficiently optimize, or give it too many restrictions,” he says. Again, it’s important to stay on top of what your machine is doing, to monitor it, give feedback and make adjustments when necessary. You’re in charge of teaching it how to serve your campaigns best. But simultaneously, you’ve got to let go and let it do its thing if you want it to thrive. 

Is There Really a Robot You Can Trust to Combine Departments, Plan Ahead, Execute Campaigns, Optimize as it Goes and Leave You with Full Control? 

Yep. It’s called Albert. 

We built it to be an AI marketing solution that’s basically your self learning ally – with over 200 skills. To give you an idea of what you can expect with Albert: 

=> You give it your KPIs, creative assets and analytics. 

=> It plans and executes your advertising strategy. You don’t have to choose which one to automate. 

=> It takes your creative assets and restructures them in a wide range of ways, so it can run countless tests across channels. 

=> You get protection mechanisms – both an account manager and a campaign monitor – to prevent unwanted mistakes. 

=> You get lots of automation, but still maintain control to verify Albert focuses on what matters most for you. 

It’s like getting more time, or an extra team member. Click here to learn more, let go of day to day tasks, and focus on business driving moves. 

What is Cross-Channel Marketing?

Hubspot defines cross-channel marketing as “blending together your various marketing channels in a way that creates logical progression for your target audience to progress from one stage to the next.” In other words, cross-channel marketing involves using different channels to make sure consistent, holistic, and seamless messaging is reaching your target audience across devices, technologies, and platforms.

The Importance of Personalized Marketing

Cross-channel marketing is the best way to reach more people, build better audience connections, and drive ROI. According to last year’s Salesforce State of Marketing report, 84% of customers say being treated like a person instead of a number is very important to winning their business. It’s so important that 69% of buyers even expect Amazon-like buying experiences – like very personalized recommendations – that only a truly cross-channel approach can deliver. Marketers have realized this need by noting it as their #1 priority; however, it’s also their top challenge. Only 49% of marketing leaders report providing an experience that completely aligns with customer expectations. High performing marketers stand out by delivering personalized messages to the right people at the right time on the right channels.

Solving Cross-Channel Complexities

Delivering personalized messaging is daunting, so many marketers avoid coordinating across paid search, social and programmatic channels due to the complexity and speed required to execute. With so many moving parts to keep track of, it can be nearly impossible for even the most sophisticated marketing teams or agencies to break down silos, sync up, and maintain consistency across audiences, campaigns and promotions.

So, how can marketers execute effective cross-channel campaigns to keep up with the rapidly changing demands of consumers? Intelligent, cross-channel marketing AI software is proving to be the only way.

Machine Learning: The Cross-Channel Answer

There are inherent limitations when people manually optimize campaigns, try to align messaging across paid channels, and aim to inform other teams about insights gleaned from campaigns. Artificial intelligence tools can manage the complexities of personalized marketing involved in cross-channel campaigns at a pace and scale not humanly possible.

Autonomous AI software can conduct time-consuming, data-intensive tasks required to compete in today’s digital advertising channels. The technology can ingest and precisely measure mass amounts of structured and unstructured data from multiple touchpoints and interactions across channels. It is technology that can learn on the fly and execute on marketers’ behalf in ways that were previously impossible. Marketers suddenly discover that it is possible to master the challenging digital advertising landscape.

Successes With AI

Albert, the world’s first autonomous marketing AI, manages cross-channel, paid digital campaigns by using a complex, multivariate approach to relentlessly evolve and optimize towards the goals marketers provide.

Within the guardrails set by an agency or brand, Albert will optimize bids, shift budgets, and test creative combinations 24/7. The intelligent machine gathers valuable insights about the customer experience in a way that has never been possible before. For example, AI can uncover ad variations that are resonating with segments of consumers at a certain stage, identify which creatives are outperforming, and unveil prospects that brands can target to increase conversions in other channels.

Additionally, Albert’s technology aligns to each brand’s source of truth to inform marketers about the contribution that each channel delivers during different customer journeys, as well as impact on total conversions. Ultimately, an AI tool like Albert helps marketers understand the most efficient paths to conversion, achieve greater visibility, and drive greater ROI.

Marketing AI isn’t just the future of digital advertising; it’s already here and is proving to be the ideal way for marketing and advertising teams to achieve cross-channel success and stay ahead of the competition.

To learn how one marketing team tied real-time insights to cross-channel digital ad campaign orchestration using Albert, read this case study.

Creativity has always been the crux of advertising. So while artificial intelligence (AI) has been routinely used across digital media buying and ad campaign automation, why haven’t marketers fully embraced AI in the creative process? A recent report by Forrester Research reveals why AI is a critical piece of the creative puzzle and offers steps brands can take to inject AI into their creative processes.

AI Will Enhance Creativity 

Using AI for creative purposes doesn’t mean robots will be writing poetic prose or designing ads. AI’s role as a key player in creative teams is to provide the insights that stimulate thinking and inspire human creativity, enhancing a creative professional’s ability to develop and execute creative ideas.

According to Forrester’s survey, 74% of creative respondents reported spending more than half of their time on tedious tasks. Leaving mundane tasks to AI will allow them to shift their focus to making creative breakthroughs by experimenting with new methods and emerging formats.

Likewise, AI’s involvement can solve bandwidth challenges. Consumers are typically exposed to hundreds of digital ads in a given day. It’s crucial to optimize content and adapt creatives for different formats to effectively connect with target audiences at every journey stage. However, marketing and advertising teams simply don’t have the time or capacity to create large volumes of content. Enter AI as a new teammate, pitching in to customize and automate the creation and distribution of mass amounts of content that marketers can then use to effectively personalize their digital campaigns at scale.

Using AI in the Creative Process

Implementing AI early on adds more data-driven analysis and measurement throughout the rest of the process. When AI is incorporated in earlier stages, CMOs can improve the creative brief and reduce guesswork for their teams.

Brands need a deep understanding of the customer journey to deliver personalized experiences for customers. This requires two things: customer journey analytics and correct signals. Armed with these two tools, marketing teams can create always-on creative content across channels, formats, and devices. CMOs who rely on powerful data and technology to fuel their insights will have more opportunities to surprise and delight their customers – especially during critical moments.

AI Surfaces Real-Time Insights

Ads with an emotional pull tend to drive greater conversions, and creativity spurs the development of engaging, emotional ads in a saturated digital ecosystem. Because the rate of creative fatigue is so high, the ability to quickly see new creative insights – and learn what is or isn’t working – can make or break digital advertising campaigns. 

For Telenor, a global telecommunications company, this ability to glean creative performance insights in real-time was a key reason why they achieved a 423% increase in ROAS. Telenor worked with Albert to run multivariate creative and media testing across its digital campaigns. Telenor’s team could continually see fresh insights from Albert to become better informed about their audiences, understand what creatives were working, and learn strategies to incorporate in future campaigns.

Deliver on Your Brand Promise

By including AI in the creative functions of marketing and advertising, CMOs can leverage AI to foster better connections with consumers, surface previously hidden customer pain points, and deliver on their brand promise. Download Forrester’s report to get recommendations for applying AI into your creative process. 

People may never be able to fully understand how AI thinks, but transparency is still needed to build trust with users and optimize the productivity of these platforms.

How important is it to understand the technology we use? Practically everybody uses a computer on a daily basis, whether at work or at home, but relatively few of us know how that computer stores files or connects to the internet. The fact of the matter is that nearly all devices today operate at such a high level of complexity that understanding their inner workings is completely impractical. What really matters is that we produce results in partnership with that technology.

But artificial intelligence is different. A huge reason behind lagging adoption of the technology is the simple fact that it is misunderstood, engulfed by numerous myths and misconceptions that cause many people to worry that it will radically change their day-to-day work processes or even take their job.

Combatting those myths will take a degree of comprehension on the part of users, despite how complex the technology may be. Though AI may be too complex for anyone to fully grasp, even a rudimentary understanding will build trust with a skeptical public.

Can Humans Really Understand Machines?

A growing school of thinkers, including technologist David Weinberger and Facebook’s head AI scientist Yann LeCun, argue that understanding an AI’s thought process is not only unnecessary, but actually detrimental to the efficacy of the technology.

The main strength of AI, Weinberger argues, is that it makes decisions based on more variables than humans are capable of considering at any given time. Since the complexity, speed, and nuance of these decisions are beyond the scope of human understanding, rendering the technology understandable or explainable to the average user would require simplifying the process in such a way that would limit its efficacy.

Optimization Over Interpretation

But of course, this doesn’t mean that AI-enabled tools should be black boxes, completely illegible to their users. Though marketers may not be able to fully understand the technical details of how AI works, it’s clear the opacity of AI makes them worry about control — our recent customer survey revealed 25.5% of marketing AI users felt they had little control over their platform’s activity. Instead, measures of transparency should be introduced that allow users to at least understand the AI’s end goal in making a decision.

No technology is perfect, and at one point or another, any system will need to be calibrated. By giving their operators a certain degree of transparency into what inspires its decisions, AI algorithms can facilitate active collaboration with humans, which will only help build trust and dispel common myths about the technology. 58% of agencies responding to our survey said they discovered new audiences with their AI, but those kinds of insights can’t happen if marketers don’t trust the information they’re getting from their autonomous partners.

That’s the motivation behind tools like Inside Albert, which we created to grant users transparency into the world’s first marketing platform built from the ground up on AI. Instead of limiting the scope of the platform, Inside Albert gives marketers the information they need to calibrate and recalibrate the way they use Albert. Any understanding of how the platform works, even if it’s limited, gives professionals the opportunity to see AI as a tool that augments their work, rather than a threat that replaces it altogether.

Before AI adoption can really surge, some degree of transparency needs to be established. The real value of AI isn’t in its algorithm or its computing power — it’s in the relationship between that power and the human operator that understands how to leverage it. But that relationship has to be based on trust, and that trust has to be based in transparency.

The digital marketing landscape is changing quickly, and ad agencies need to adapt if they want to stay relevant.

Executing a highly personalized marketing campaign across a variety of channels is more challenging and complex today than ever before. For many companies, the knee-jerk reaction to this deepening complexity is to turn to an advertising agency for expert assistance. In certain circumstances this can still be an effective move, but it’s no longer the kind of common sense choice it was when print, television, and out-of-home advertising dominated the industry.

As Albert™ CEO Or Shani points out in CMO, “The role of the media buyer as middleman in digital ad buying is very different from the role of middlemen in traditional media.” If companies fail to adjust their relationships with ad agencies and media buyers, Shani continues, “advertisers put themselves at risk of absorbing even more costs in the form of marked-up prices at the bid level — or of the entire service provided by partners.”

As such, marketers looking to choose an agency partner must take a strategic approach to the selection process by making sure that each candidate is capable of providing value in today’s marketing environment, not the marketing environment of the past. Ad agencies that have truly kept up with the times will check all three of the boxes outlined below.

A Demonstrated “Right-Fit” Track Record

At the end of the day, “marketing” is a catch-all term that can take on significantly different meanings in different sectors. A heavy industry manufacturer may need to advertise just as much as a restaurant does, but this doesn’t mean that the same ad agency will be the right fit for both. When choosing an agency partner, a company should carefully examine candidates’ backgrounds to ensure that a potential partner has a demonstrated record of success in the company’s specific field.

This holds true not only for industry expertise, but for account size as well. If your company would be an agency’s largest or smallest account, this should prompt you to reconsider the decision to commit. Is the agency capable of handling a campaign portfolio this large? Conversely, is the agency nimble enough to meet the needs of a portfolio this small? Account size shouldn’t always be a disqualifying factor in and of itself, but it’s vitally important to consider.

A Capacity for Predictive Insights

As the volume of data bearing upon critical marketing decisions grows, strong data analytics will become increasingly important. When it comes to evaluating both specific ad performance and broader campaign effectiveness, a company’s agency partner will often be the only one with all of the data necessary to perform the requisite calculations.

Unfortunately, these evaluations tend to only go as far as a rundown of metrics like impressions, ad clicks, starts and stops, and click-through rates. While these metrics certainly help paint a broader picture of overall campaign performance, they don’t provide companies much in terms of forward-looking insight. True campaign optimization can only occur when a company is able to surface and act on predictive insights, in real-time, like those provided by autonomous tools like Albert. By implementing this kind of AI tech, companies can begin to understand what is likely to happen in the future, not just what has already happened.

Completely Transparent Operations

According to the Association of National Advertisers’ industry-shaking 2016 Media Transparency Report, “Numerous non-transparent business practices, including cash rebates to media agencies, were found to be pervasive in the U.S. media ad buying ecosystem.” When agencies are compelled by these suspect incentive structures to repeatedly direct their clients’ ad spend toward media that may not actually be in the clients’ best interests, the entire purpose of an agency partnership begins to break down.

As such, companies must do everything they can to ensure that the agency partner is organized and dedicated to delivering positive outcomes, not claiming kickbacks or rebates from ad publishers.

More often than not, this will include a willingness on the part of the agency to work alongside an AI platform like Albert. Artificial intelligence marketing tools make marketing more efficient, and an agency that refuses to recognize this value is unlikely to be a good partner for any company hoping to stand out from its competition.

At a recent iMedia event, Naomi Simson, Co-founder of the Big Red Group, interviewed Angela Greenwood, Director, Acquisition & Customer Marketing at Optus, about her thoughts on:

• The future of marketing – and our addiction to attribution
• The role AI will play – and what people fear the most
• A marketer’s priorities, a melding of analytics, creative and the big idea.

Naomi Simson: At Optus, there was a real sense of urgency driving the implementation of AI technology. What were the commercial drivers behind this strategic direction?

Angela Greenwood: It was a few things. It can be very, very difficult for us to understand what the right level of investment across channels is in digital, and how we move money between these in real-time. Often, it’s very much a siloed approach to how much investment we’re putting into each digital media channel. We wanted to understand if we gave an autonomous AI tool the freedom to move funds between all those channels, and to serve the ‘right’ creative in real-time, what would happen? So there was a healthy amount of curiosity about what we could achieve.

NS: In a marketing environment where the open web is becoming a thing of the past and we’re dealing with the ‘Walled Gardens’ – each of them claiming they ‘own the customer’ – the notion of attribution becomes even more complicated. We as marketers focus so heavily on attribution, so what was that conversation like on your journey to AI

AG: We still have a very healthy interest in attribution. We still put a lot of effort into investigating effectiveness – but you can only ever look at that retrospectively, not future-facing. And for us, the amount of sessions we attribute to one single channel –  when we know that a customer’s journey is way more complex than that – means we can get really tripped up on thinking one channel or piece of creative is more or less effective than it is in reality. What we’ve been able to see with AI is that some of the creative constructs that work today, no longer work tomorrow – so we want to be able to see that in real-time.

NS: Being able to test ideas at scale was one of the driving factors that attracted you to Albert AI. Tell us about that.

AG: AI can take a lot of the heavy lifting away from some of the lower-level tasks around digital media buying. But what it actually creates is a lot more tasks around how you feed this engine with enough creative to be able to personalize at scale to prospecting leads. Because the possibilities are endless – they’re only really limited by what we’re able to put out there.

NS: Let’s talk about the agency relationship, and the human side of AI and what it means for the people on the team and their concerns and challenges.

AG: I was pretty concerned and challenged myself. As performance marketers, we have a bit of a reputation for being just a little controlling, so to be able to go from a very detailed digital marketing plan that’s broken down to the nth degree, to a single line item that says, ‘here are the dollars, go do’, that’s terrifying. It was really important to get the set-up right. We had to get back to basic things like getting our naming conventions right and making sure all of our campaign structures were set up correctly.

NS: I can imagine there was a lot of fear for the individuals involved – but as you’ve noted it’s really the low-hanging fruit that AI takes care of, to really free up the people to focus on those interesting strategies and learning pieces. Tell us about that journey for your people, and your agencies, and how they shifted from the execution to the strategy.

AG: It will never cease to amaze me how much people will cling to low-value tasks. So once you separate your people and your agencies from all that, you free yourselves up to think more strategically – like how we’re going to tailor our value propositions to different audiences, how can we actually do that really personalized creative at scale, and how can we take the insights we’re getting from the engine and do something with it? And that’s the really big step that we’ve been able to take. And also, because this type of tool works very fluidly across all the different digital channels, it has actually opened up opportunities for our internal teams to become more cross-functional, and they’re now thinking much more holistically about the customer journey.

NS: What does success in marketing look like for Optus?

AG: It’s a number of things. We want to be as efficient as possible. Digital still pays a really massive role in driving brand consideration, but it’s also really important for us to keep building the top of the funnel through that activity. It’s really important with an AI solution that you’re actually pointing in the right direction – because if you feed it the wrong signals and optimise towards the wrong thing, it will go really hard after the wrong thing. So that’s been a really important learning – how do we make sure that we’re actually optimizing the right activity to the right result? And that’s never going to be uniform across everything that we do.

NS: Let’s talk about cookies. We didn’t just set this up for now, we wanted to plan for the future – so how does this AI solution deal with privacy issues and knowing who your customers are?

AG: For advertisers, the most important thing we can do is make the most of all our first-party data, and being a telco, that’s a unique position to be in. We do actually have a fair bit of that, so for us, it’s about how we can we utilize that first-party data for the AI to find suitable look-a-like audiences. And then how do we incentivize uses to engage with our own platforms? How do we ensure we get more people using our app so that we are not dependent on the outside world for that view of our customer.

NS: Do you have any particular campaigns you have run that have helped you identify intent to purchase?

AG: Where we see value in Albert and how some of our assumptions have been challenged is around thinking that certain audiences have intent for a certain product, and how Albert then runs through a full range and offers alternatives. We’ve actually found some really interesting crossovers between audiences in terms of intent that we never would have understood before Albert. For example, if someone has intent to buy a post-paid mobile, they actually have a strong intent for accessories as well, so then how do we capture that as part of the ongoing conversation with that customer?

NS: That’s what AI does particularly well – it’s looking for, based on certain previous behaviors, that intention data, and taking all of that information to start predicting ‘what next?’ It’s almost impossible for a human to do that.

AG: You would need a massive team of data scientists to achieve anything similar at scale. And anyone who’s tried to hire a data scientist knows how hard that is. Albert enables us to do all this very rapidly.

“We have had a very established test and learn program at Optus for many years, but the speed now and the scale at which we can get those insights is just so much faster now. We are an incredibly competitive category – telco is a blood sport, and it’s very much about how you gain market share and take market share from competitors. So we will do anything we can to get a competitive advantage.”

NS: What does the future look like for Optus and your AI journey? And I’m talking no more than the next 6-12 months.

AG: For us it’s about how do we get more signals in? How can we get more data in for that to work for us? How do we do a better job of ingesting offline data to optimize towards an omnichannel result, and how do we better leverage our first-party data? And it’s also about the creative side – we have only dipped our toes in terms of what Albert is able to do when it comes to creative optimization, so for us, it’s about how we set up so many different creative variants to be able to really maximize results.

“Don’t fear the machines. It frees us to be more creative and more strategic and that’s a win for the client and agencies.” – Angela Greenwood.

Read how other clients used Albert’s AI capabilities to fuel their digital marketing and advertising

Albert is distributed in Australia by Marketics, a wholly owned subsidiary of the Big Red Group. This interview was originally published by Naomi Simson.