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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.

Artificial intelligence (AI) is sometimes confused with automation, and the terms are often used interchangeably. When talking to vendors, it’s critical for digital marketers to decipher exactly what’s being offered so you know it will truly address your needs. Today, let’s demystify these terms and discover what happens when the two are combined.

Differences Between Automation and AI:

Robotic Process Automation (RPA) software is great for simple activities and repetitive tasks that follow instructions or workflows set by individuals. It is best suited for highly repetitive and predictable tasks. Automated tools require manual configuration and human supervision to effectively execute campaigns. The trick with RPA is for humans to anticipate every permutation so the machine is programmed to behave the right way every time. This is why constant vigilance is required. If the environment changes, marketers must manually step in and make the necessary adjustments.

AI refers to how computer systems can use huge amounts of data to imitate human intelligence and reasoning, allowing the system to learn, predict and recommend what to do next. An AI capable of understanding marketing KPIs can use various algorithms that act in concert to find signal in the noise of data and find paths to solutions that no human would be capable of. Most AI today works in an assistive fashion, providing next best action recommendations to humans who then decide whether to trust them or not and then manually make adjustments.

Combining AI & Automation: Sweet Treat!

When robotic process automation is combined with elements of AI such as machine learning, the result is known as intelligent process automation (IPA). An IPA tool is powerful because it allows us to reap both the benefits of automation – increased speed, efficiency, time-savings, and ability to scale – with the insights, flexibility, and processing power of AI.

Marketers who use IPA are able to augment their capabilities, while off-loading repetitive campaign management tasks to the machine. It’s different from pure robotic automation in that the AI can start, stop or even alter what it is doing based on the environment in which it operates. What’s more, because the best AI systems allow marketers to set guardrails, there’s no chance of unforeseen events taking outcomes too far astray. For marketers, this means faster, more personalized execution and processes, greater use and accuracy in data, and improvements in overall customer experience. Marketers shift from fussing over bid adjustments and budget allocations to higher value add, human-centric contributions like, “how do we evolve our value proposition to drive more business?” Because of these clear benefits, Forrester predicts that by 2020, 25% of Fortune 500 companies will report hundreds of examples of IPA use cases.

Benefits of AI + Automation for Marketers

IPA technologies not only surface insights for marketers but actually turn insights into action. For example, Albert can synthesize historical digital campaign data across channels, craft strategies for execution, and explore different combinations of messages, creatives, and frequency across audiences. Evolving relentlessly over time, the intelligent machine’s autonomous capabilities allow it to actually shift budgets, adjust bids, audiences and optimize campaigns 24×7 in relentless pursuit of KPIs that a marketer has set.

This is especially important as customers continue to demand more from brands; Salesforce’s Fifth Annual State of Marketing Report revealed that 53% of customers now expect personalized offers, and 62% expect businesses to anticipate their needs. IPA technologies are becoming the only way to deliver personalized touchpoints for an optimal customer experience across paid digital channels.

Key Takeaways

Implementing intelligent process automation can help marketers achieve better paid digital campaign results while surfacing customer, media and market insights that inform not just marketers, but the overarching business strategy. In the face of potential economic slowdowns or other unforeseen external market conditions, marketers are finding that new technologies like IPAs can help them innovate, scale and increase efficiencies to stay competitive.

To learn more about how Albert plans, executes and optimizes paid digital marketing campaigns, contact us.

Each of your customers is unique, and each has different expectations and needs when it comes to experiencing your brand. Here’s how you can offer every one of them a unique digital experience.

“Customer experience” is a term that practically everyone in the business world is using, but is frustratingly difficult to define. Some might think of a seamless smartphone interface when asked to explain what a positive customer experience is, for instance — others might focus on the customer service side of a brick and mortar retail space.

But the fact of the matter is that defining customer experience by a singular interface ignores a fundamental truth about today’s omnichannel market. A customer’s experience isn’t just defined by how much they like your store, or how easily they can access your website. Rather, it’s a grand total of all their interactions with your brand, whether they’re visiting you in person, on your website, or via social media, or reviewing their invoice, or chatting with a customer service representative. As HBR contributor Adam Richardson points out, customer experience isn’t just a snapshot in time: it describes the entire arc of that customer’s engagement.

That being said, digital media is constantly giving us new ways of understanding and engaging with customers, raising their standards for experiences of your brand every day. Even if you already have the in-person experience down to a science, without the proper digital tools, customers will come away feeling that they haven’t received the best possible service. Here are a few suggestions from Lithium Technologies VP Dayle Hall that can help your company deliver the kind of high-quality digital experience your customers are looking for:

1) Be An Active Listener

One of the first things Hall notes in his article is that simply listening to what your customers say isn’t enough — it’s only by engaging in social listening that brands can set themselves apart from the competition. When customers take to social media to voice their feelings or ask a question, writing back goes a long way towards making customers feel like they’re really being heard, even if it’s just to say “thanks!”

2) Create a Conversation

If you’re really looking to curate an impactful online experience, it’s critical that you do the proactive work of creating a conversation with your consumers rather than passively waiting for them to interact with you.

Remember, though, that a monologue is not a conversation. Just posting articles or writing tweets won’t do you any good if there’s no one on the other end who wants to respond to them. This is where the listening can help you: if you’ve been paying attention to the kinds of content your customers want to see, it’ll be much easier for you to encourage debate, prompt questions, and provide them with valuable, personalized insights.

3) Keep Customers on Their Toes

In a seemingly-endless digital sphere, consumers are constantly deluged with new content. That means they’re much harder to surprise and delight, as Hall puts it. In order to create a positive experience, you’ll first have to create a memorable one. Before engaging in any digital action with consumers, Hall recommends asking yourself “will this digital moment make a customer smile?” The key, as with most marketing, is generally to stick to your guns: curate a unique voice and perspective for your brand, and if it’s original and endearing, everything else should follow.

4) Always Have a Plan B

In a perfect world, you’d never have to turn the tide of consumer opinion — in the real world, it’s critical to have a backup plan in case your PR strategy goes awry. The amazing thing about the internet is that you can respond in real-time to consumers, so the minute things get hairy, your first line of defense will always be the digital sphere. Always be ready to turn a not-so-great news story into a positive customer experience.

Powerful Platforms for Powerful Digital Experiences

Of course, when you’re looking to conquer the digital space, it’s helpful to have a high-tech digital solution in place. For the best results, AI-powered marketing platforms like Albert create powerful digital experiences by hyper-targeting user segments and catering content based on their specific needs and behavior. By leveraging the use of autonomous digital tools with the ability to detect trends and insights that are all but invisible to the human eye, you can much more efficiently and seamlessly create a positive customer experience, even in today’s crowded media landscape.

A good digital experience (DX) is one of the most important components of a modern marketing strategy, but it’s difficult to achieve without the help of a powerful AI tool.

Though there are countless other examples spanning just about every market niche imaginable, Uber is perhaps the quintessential case of an exemplary user experience compensating for an unremarkable product. Despite offering more or less the same core service as taxis and other car-for-hire outfits at a similar price point, Uber has managed to go from small startup to $100 billion industry-leader in the course of a single decade.

This incredible success can largely be attributed to the usability of Uber’s app and the top-of-the-line brand experience the company delivers to its customers. Stories like Uber’s drive home the point that, in today’s marketplace, a good user experience is just as important as a quality product and competitive pricing.

A Deafening Digital World

The value of a top-notch user experience has been heightened greatly by the rise of digital tech, which has greatly increased the portion of time consumers spend engaging with media. Research indicates that the average smartphone user touches their phone 2,617 times per day, a figure that can rise to as high as 5,400 touches among particularly active users. As such, a poor or unmemorable user experience gets quickly drowned out by the constant barrage of information to which the modern consumer is exposed.

In order to survive and thrive in this kind of landscape, companies have no choice but to create a comprehensive, engaging digital experience (DX) for each and every one of its potential customers. Building a brand involves more than an eye-catching logo and an attractive core offering: it’s about articulating a purpose, eliciting emotions, delivering interactive experiences, enabling new behaviors, and inspiring social connections.

Collectively, these brand-building endeavors amount to the creation of a fully-realized digital experience, and are often the decisive factor in a company’s success or failure.

The Inherent Complexity of Modern DX

A good DX is not restricted to a single, make-or-break marketing touchpoint, however. In fact, it covers a customer’s entire experience with a brand in the context of their unique digital environment, from online ad campaigns, to the company’s website, to reviews on third-party sites, to text or email purchase confirmations. Consumers do not experience any brand in a vacuum, and marketers must take all of the digital noise occurring around the brand’s touchpoints into account when crafting their DX.

Unfortunately, the sheer number of channels and devices on which consumers experience branded content makes it difficult to predict how a DX strategy will play out and undermines your ability to measure its success once it has been implemented. No matter how experienced a marketing team may be, it simply isn’t humanly possible for a team to collect, track, and analyze the millions of data points necessary to define specific customer journeys across digital channels.

Building a Strong DX with AI

Thankfully, cutting-edge tools like Albert™, the world’s first fully-autonomous marketing platform, can help marketers overcome the obstacles presented by today’s oversaturated digital spaces, as well as craft and deliver a high-quality DX to each unique customer.

By leveraging his advanced artificial intelligence capabilities, Albert organically understands customer journeys across all channels and devices. That liberates marketers from much of the time-consuming busywork that holds them back from generating more compelling creative materials and producing a DX that will stand out from the crowd.

Ultimately, as Uber and others have shown, modern marketing comes down to quality of interactions more than quantity of touchpoints. An engaging DX is the central component of a quality-over-quantity approach to marketing, and is therefore absolutely essential for any brand hoping to establish itself as a leader in an increasingly overcrowded marketplace.

At Albert, we can already see that in the very near future, all paid digital campaigns will be executed by autonomous artificial intelligence (AI) guided by marketers. Through our experience helping Fortune 500 clients on their journey toward overall business transformation, we’ve discovered the following insights that might be of interest to brands who are thinking about implementing an autonomous, cross-channel AI marketing solution like Albert.

Why Collaborate With A Machine?

People have unique strengths. We can empathize, be creative, or be inspired to come up with ideas seemingly out of thin air. On the other hand, an AI-powered machine can transact, iterate, predict, and adapt to changing conditions at a pace beyond our comprehension. When marketers collaborate with an intelligent machine, the AI empowers them to expand their reach far beyond the capability of traditional advertising technology. Today, a machine acting intelligently on behalf of marketers can paradoxically enable a brand to present itself as more human, personalized, and flexible. 

When marketers implement autonomous AI, it means that instead of operating the technology, they start to collaborate with it. This often involves shifts in a team’s mindset — especially for those with sophisticated domain expertise. Machines take a different path than humans would, because they can focus on everything at once, as opposed to the way we work, balancing just a few variables in order to find performance. As a result, it is important for brands adopting AI tools to ensure that implementation not only integrates technology but people as well.

Digital Marketers Get To Shift Their Focus

Marketers who adopt autonomous AI are not always prepared for subsequent shifts in thinking required by the human team. Insights gleaned from an AI tool may surface learnings that shed light on previously undiscovered patterns or insights that change a team’s priorities or strategy. For instance, what does it mean that the machine uncovered a new audience the marketers didn’t know they had? Or what are the implications of hundreds or thousands of long-tail terms that the machine is able to make perform profitably? When brands adopt AI to take on rote, repetitive campaign management chores, marketers find they are able to use their traditional marketing strategy and creative skills to unearth the meaning of the AI’s discoveries, find stories in the data, and craft compelling value propositions from them.

Surprise Becomes a Way of Life

Brands often encounter startling revelations when first implementing autonomous AI. For example, rather than crunching campaign data, more energy starts to be spent on making decisions related to what creative elements should be provided to the AI as well as thinking about overall campaign direction. Because the AI tool’s cross-channel capabilities deliver messages to the right person at the right time, human expertise can be redirected from a narrow focus on bid, audience, and budget allocation tactics to asking more strategic questions such as: are my messages resonating? And, is my overall marketing working?

Additionally, the rate of creative fatigue can be eye-opening for brands. Because the machine offers scaled capacity to efficiently test creative iterations at a pace that was never before possible, teams get to test as many variations and ideas as they can create. Marketers find suddenly they can test and learn more quickly, understand when to use a rational or an emotional proposition, and develop ever more learning agendas to feed the intelligent machine. Unlocking actionable insights and discoveries often steers teams to try new entirely creative techniques and tactics.

Similarly, the process of reviewing campaign performance speeds up to real-time from once a week (or month). And suddenly, those reports are actionable. In pursuit of performance, the AI may request more budget in one place while limiting spend in another. Or, the system may inform that engagement with one audience is increasing far beyond another, so it begins looking for more of the same in other ways. Marketers are on point to think about what opportunities this creates for other parts of their business.

AI Implementation Takeaways:

Overall, we’ve found that implementing an AI creates new vistas for marketers to return to their roots: storytelling, using creativity, and building value propositions that resonate with consumers.

While the implementation is fast, learning how to fully utilize an autonomous AI to deliver on the promise of business transformation takes time. But, with adequate planning and preparation of staff, companies can speed up their path toward successful human+machine collaboration.

To learn more tips about autonomous AI, download this commissioned report conducted by Forrester.