Are humans the flaw in the AI machine?

With many predicting that 2018 will be a watershed year for artificial intelligence (AI) and machine learning (ML), we might expect that marketers will find their jobs becoming easier over the next 12 months. However, our plans to let technology take the strain could be at risk if we lose faith in these new techniques without first giving them enough time or attention.

There are plenty of people in advertising who question the impact that AIwill have on the industry as a whole and dismiss discussion around the subject as simply hype. Many argue that the usefulness of AI and ML will be limited to a few niche areas of the industry. There does, however, seem to be a consensus that brand safety is one of the areas where these relatively new technologies can have a real impact.

We must be wary of the belief that AI and ML are magic bullets that will instantly fix programmatic’s brand safety issue. To enable us to get the most from AI and ML techniques, we must first ensure that we as marketers fully understand what our ultimate objectives are.

Of course, the aim is to eliminate the issue of ads being placed alongside content that is inappropriate, but further to this it is achieving KPIs.

Brand safety

When it comes to brand safety, there is no universal definition that fits every brand. It’s a subjective area – while most brands will obviously want to avoid placements alongside extremist and illegal content, it’s more difficult to come up with hard and fast rules as to what kinds of content are controversial or inappropriate without approaching it on a brand-by-brand basis.

For example, a soft drinks company wouldn’t want to have its ads appear on a website offering information about diabetes; nor would a kitchen knife manufacturer want its advertising accompanying a news article about violent crime.

Many current technological solutions used in an attempt to ensure brand safety, such as keyword searching, blacklisting and whitelisting, often fall short by either letting some ads slip through the net, or blocking placements that would have been perfectly safe – also known as a false positive. In the long term these outdated techniques do not have the capabilities to provide brand safety protection, as they are less adaptable to individual brand needs and incapable of understanding nuances in meaning at the page level. Therefore, taking a more refined approach by using AI-based technologies such as semantic analysis and Natural Language Processing to gain a better understanding of emotion and context is essential.

Google, for example, has been using AI to ensure YouTube content is safefor its advertisers, saying that the technology allows it to identify and remove unwanted content quicker than a human could. More than150,000 violent videos have been wiped from the site within just six months, according to Google – and this just the start. This progress is obviously welcome after the multitude of brand safety scandals it suffered in 2017, and shows the potential benefits of scale from employing AI solutions.

Full context

Brands understand what content could threaten their reputation but the task of implementing such tailored brand safety measures across every ad placement, is where the complexity begins. Adopting a one-size-fits all solution does not accommodate for effectively protecting the brand while maximising relevant ad placements.

This is where utilising AI technologies to process large amounts of data at speed and scale to combat inappropriate placements and missed opportunities is key, but these techniques will only ever be as good as the rules and variables that humans set for them.

While some brands’ reaction to the YouTube Brand Safety scare was toshift their focus from programmatic to native advertising, a better response would be to update their approach to this type of advertising. Blacklists, whitelists and keyword searches are not a long-term solution to brand safety – we need to build algorithms that understand nuance and context, and can continue to learn and refine themselves.

Solutions such as semantic analysis provides the ability to understand the full context of a page, reducing the risk of a brand missing out on a golden advertising opportunity due to a false positive, while ensuring inappropriate placements are avoided.

Persisting with outdated methods that are not up to standard instead of embracing AI technological solutions – or abandoning programmatic altogether – holds back the advancement of AI as an effective tool to ensure brand safety. The perception that semantic technologies are more complex for advertisers to use are also a misnomer. If anything, they are much simpler to use given there is no need for the manual inclusion or removal of keywords when trying to optimise in the real world.

Although the industry’s perception of AI and ML is one of increased automation, we have to realise that these technologies are very much under our control. To advance programmatic, we need to ensure we fully understand brand safety within the context of an individual brand, rather than attempting to use broad brush strokes for the whole industry.

These learnings must then be applied to the AI and ML algorithms we use to make sure ad placements are appropriate for the brand. Otherwise, we will continue to hold back the development of AI, and in turn the entire industry as brand safety remains unachievable at the scale needed to succeed.

– by Nick Welch

How to lose friends and alienate people: Why brands can’t get lazy with social media

Facebook doesn’t have a lot of friends right now. Fresh revelations are coming to light over the Cambridge Analytica scandal and it was reported that the data of 87 million users were improperly shared with the political consultancy firm.

I’ve argued elsewhere that we shouldn’t give up on social media in the wake of this debacle but that doesn’t mean there aren’t lessons to be learned from recent events. As a brand, removing yourself from Facebook and social media would be both foolish and impractical, but companies do need to take this opportunity to shake up their digital marketing offering. Social media isn’t a one-time tick box you can check off with the help of a few scheduled posts. It’s a constantly evolving sphere and to keep relevant, companies need to keep up.

Diversification is the name of the game for brands. While it’s doubtful Facebook will disappear from our lives any time soon, brands need to remember the lesson of Cambridge Analytica and realise you shouldn’t put all your eggs in one basket. It’s vital to utilise a wide variety of different broadcasting platforms to promote your content. This not only increases your brand’s online presence but allows you to tap into the different demographics available on each platform. Don’t think the same audience exists on Twitter as on Twitch.

And there’s a host of different broadcasting competitors out there when it comes to releasing your videos. Facebook’s biggest competitors are obviously YouTube and Twitter, with all three social media giants currently investing heavily in their live streaming options. The failures of Facebook will have pushed users to previously unconsidered platforms, and brands need to re-follow them if they don’t want to lose out.

Although it’s expected that for video, YouTube will be the biggest winner from the Facebook fallout, digital marketers shouldn’t dismiss the alternate options available. Twitch, the live streaming platform primarily used for eSports, hit headlines recently when infamous YouTuber Logan Paul launched a channel and gained 190,000 followers in 24 hours. The move generated upset from regular Twitch-ers who felt Paul’s presence would sully its name but it ultimately demonstrated that all savvy content creators are constantly looking to increase their digital footprint.

Periscope is another broadcast option whose full potential has yet to be realised by users and digital marketers alike. It was launched in 2015 and allows users to live stream from a mobile device anytime and anywhere, sharing content with viewers who join your broadcast. There’s also, the new social broadcasting app on the block, set up to rival Twitch but with a more ‘personal experience’. And I’ve no doubt we’ll soon be seeing many more besides, including from China and other successful markets. Niche platforms are also emerging, with live shopping channels, like TalkShopLive and ShopShops, gaining popularity

Diversifying broadcast platform options is a way of empowering the content creator and taking control back from tech giants. Stream Time’s vision is for a digital world where the creator is put first and can own their audience, directing them to wherever they want to go and choosing when and where to go live. Increasing your broadcast options doesn’t have to mean spreading yourself thin, if properly managed.

Facebook’s lesson is that now, more than ever, we need to be serious about social media. Refusing to be lazy with your marketing strategy is what will be putting certain brands ahead of others. There are massive social media opportunities available but companies and creators need to be proactive if they are to reap the rewards.

– by Trevor Evans

Black Friday: There’s an elephant in the room


From a brand marketing point of view Black Friday is a disaster – it’s short termism at it’s worst, with little or no regard for the long term damage to reputation and profitability.

Stand back and look at it dispassionately, and it’s crazy that a frantic day of knock down prices and brawls over flat screen TVs was ever seen as holding the key to tipping into annual profit.

A different approach

In truth Black Friday is a not-so-subtle hint that a different approach is required.

But that’s the elephant in the room – rather than cutting prices and relying on flash sales, retail could finally find a way to more effectively monetise vast ecommerce traffic year round.

And let’s be clear, we’re not talking about overnight transformation – the clue is in the numbers.

Shoppers spent £1.1bn on Black Friday in 2015.  But, spread that headline-grabbing £1.1bn over a year and it equates to just £21m a week. To put that figure in context, it amounts to an increase of just 0.3% on the sector’s average weekly revenues (excluding the £1.1bn from Black Friday).

Are we really to believe that retail cannot find a way to drive revenue increases of just 0.3%?

Conversion failure

Given the relatively low levels of conversion online right now, such a modest gain is eminently doable. Let’s remember that, in 2015, ecommerce revenues of  £114bn represented a conversion rate of around 7%.

In fact, despite massive spending on ecommerce marketing and merchandising technologies over the years, conversion rates have stubbornly remained well below the 10% mark since ecommerce’s year dot – and lag well behind in-store rates.

That failure is down to merchandising and the user experience – ecommerce sites have failed to inspire people to buy or made it too hard to buy, or both.

A rethink

The core problem is a reliance on offline techniques that simply do not work online – a rethink is required.  At present, retailers still rely on a manual approach to merchandising that is unsustainably labour intensive.

Unsustainable in terms of resource demand – just look at the sheer number of online merchandising jobs retailers are currently trying to fill.

And unsustainable in terms of results – how long will retailers continue to attempt to prop up results with sticking plaster solutions and promotions rather than address the core issues?

Automation and AI

The truth is, this is the essence of a marketing (well, merchandising) technology problem.  Retailers are failing to grasp a nettle that other sectors tackled long ago – automation.

But not just any automation.  The automation of online merchandising’s heavy lifting – the vast number of repetitive but vital tasks that are practically made for machines – and automation guided by artificial intelligence and big data capabilities.

This kind of intelligent automation has two immediate virtues.

Chief amongst them is the ability to deliver better, more relevant experiences for each customer, by adapting everything from search and navigation to recommendations and even product display according to individual behaviour and intention in real time.

That would truly be a watershed moment: The moment when retailers finally embrace the full potential of ecommerce – the ability to shape and instantly adapt product discovery and the entire customer experience according to the needs of each and every individual customer.

Doing all that across product exposure, search, navigation and recommendation of course, neatly takes care of both inspiration and ease of use – the twin failings that have to date held back conversion rates.

Meanwhile, merchandisers are freed from the spreadsheet, and enabled to focus on the high level tasks that really require their specialist input.

That could include the development and execution of the holistic product exposure strategies that would be necessary to guide automated merchandising.  These high level strategies could be shaped by real merchandising priorities – business objectives like revenue, profit margin, stock oversupply and consumer trends (be they micro or macro).

Kick the habit

When you think about it, an ecommerce operation that brings together marketing and technology to cut costs, create efficiencies and improve sales performance is just what retailers should have been doing all along.

In their defence, of course, the AI-enabled technologies that truly enable it are only just emerging, so the real challenge now is to kick the habits of the past and look to a different future – a future in which ecommerce experiences inspires purchase through absolute, individual relevance.

Viewed through that lens, a revenue gain of 0.3% suddenly feels more like a molehill than a mountain – and, thank goodness, that race to the bottom of which Black Friday is so emblematic would be a thing of the past.

– by Frank Schoutissen

It’s time to unleash clickstream data to turn browsers into buyers


Online retailers struggle with two major problems: abandoned shopping carts and browsers who don’t turn into buyers. With 74% of online shopping carts being abandoned worldwide, it’s clear that many marketers are overlooking the solution: clickstream analysis.

Wholesalers are famous for great deals — because who doesn’t need a gallon of mustard or 1,000 Advil? But they have an abandoned cart issue. Our team has seen that wholesalers typically see 50% to 65% of their carts abandoned. Even Costco, which dominates the space, converts only one out of every two shoppers into purchasers. Sam’s Club might be happy about its 35% completion rate — until it learns that Costco is at 50%.

J. Crew committed to clickstream analysis as far back as 2001 to drive product recommendations for non-buyers and grew its online sales by 22% over the next six months. Since then, its online presence has continued to grow; in last year’s fourth quarter, the company posted a 4%increase, hitting $247.8 million.

How clickstream helps solve the abandoned shopping cart

Clickstream data isn’t simply a nice-to-have — failing to use it could have serious consequences for forward-thinking businesses. With just 37% of consumers agreeing that their preferred brands understand them, marketers are struggling.

There are many tools to measure how effectively a marketing program drives website traffic and on-site transactions, but brands should budget properly by accounting for off-site transactions, too. Examining clickstream activity allows you to segment customers and analyze which sites they visit before and after yours. It can also help you identify organic keywords, traffic drivers, and conversions industrywide.

While user experience teams know how their own path-to-purchase funnels operate based on internal web analytics, they’re seeing limited views of how marketing campaigns are doing. Clickstream data expands the picture. To reap the benefits clickstream analysis can provide and to put an end to abandoned shopping carts, marketers should:

See where customers came from

Whether the final touchpoint is a transaction confirmation or an account registration completion, check out the last 10 pre-visit touchpoints (i.e., previously visited websites). Tools like Google Analytics reveal only the referring URL customers came from, but clickstream data shows all the steps before that in a customer’s journey.

After analysing trends for highest volume or common paths, list the websites and companies appearing most often. Then set up a strategy to determine which channel will have the most engagement — whether it’s affiliate, display, or data feeds — and either include targeting options or reach out to the companies identified via the clickstream data.

Watch where customers go afterwards

Do visitors conduct more research after leaving the website? Do they visit a competitor’s page? Web analytics alone don’t answer these questions. Clickstream data analysis can, which provides valuable information for re-engaging audience members to convert them into buyers and to foster relationships. If a third-party marketplace is the next stop on their browsing journey, that’s the site to target. By following the same path of action for post-visit touchpoints as pre-visit, you can better identify customer behavior after a transaction has been completed.

Cabela’s, for one, has been using clickstream data to analyse customer browsing patterns for years. Observing both pre- and post-touchpoint behavior, the marketing team discovered that one in three customers will browse before committing to a purchase, and that conversion rate actually increases the longer a customer browses. The company tested campaign variations for each product category until it landed on a tactic that worked: An email campaign centering on camping merchandise increased sales by 20% companywide.

Measure third-party lift

Identify the marketing campaign to measure, the distribution sites where the merchandise is sold, and the desired purchase window. Then, crunch the clickstream data (or partner with a company that can) and report on total transaction counts influenced by the campaign or the overall lift in the conversion rate if those third-party conversions were taken into account. Leverage your CRM or business model based on these conversions to understand proper attribution weights.

Hotels, for example, can use this method to gain ground in the war for direct bookings against online travel agencies. A hotel would place higher value on a reservation made on its own site than on one placed through a booking site like Expedia because it wouldn’t pay commission.

Segment customers across industries

Most marketers segment their customers, but do they segment their competitors’ customers, too? Clickstream allows for this possibility. Identify the sites that appear most commonly in browsing activity, and look at the overlap across the industry. Use this data to influence channel selection for future marketing efforts.

Nike’s Product Listing Ads, for instance, might drive transactions on, but do they influence customers shopping on Amazon’s or Foot Locker’s site? Clickstream data makes it easy to see the connection, providing a more accurate measure of the program’s success and helping to drive future budget decisions. It can also help identify new opportunities. Which sites have competitors failed to notice that customers visit?

Target the right audience

Upgrading to audience buying is much simpler with clickstream data. When using a data management platform or a demand-side platform like MediaMath or Quantcast, you can buy and target customer audiences developed from clickstream activity seeds for programmatic campaigns. These audiences vary between a standard set — people who have purchased from top 10 retailers, for example — and ones that are customisable.

Whether it’s audience buying or debuting a new platform, clickstream data analysis can help identify new opportunities by giving truly granular views of customer segments. Analyse customers’ clicks to see what consumers are looking for that the competition can’t offer, then align programmatic campaigns and audience-buying endeavors with these opportunities.

Clickstream data is a vital tool in the battle to protect and expand market share. While internal metrics might suggest a rosy picture, an industry comparison reveals the bigger picture — and companies can’t afford to keep losing three-quarters of their prospective customers.

– by Deren Baker

Four ways to create a unified customer experience in a post-channel world


Every marketer knows the route to true consumer engagement no longer runs along a single path. An explosion of innovative technologies, channels, and formats has created a complex, connected ecosystem where interactions are fragmented and unrestricted. Keeping up with the needs and wants of today’s consumers through the delivery of timely, relevant marketing communications requires marketers to convert ever-expanding streams of user data into actionable strategies.

Yet by setting their sights on ‘multi-channel’ communication as an end goal, digital marketers are trying to solve the wrong problem. With so much focus on splitting campaigns across channels, most have failed to notice we have now entered a new world where, for consumers, there are no borders. In this post-channel world, the customer is at the epicenter of all activity and campaigns are not just about maintaining a broad brand presence, but also providing a unified experience that offers plenty of opportunities for cross-selling, up-selling, and boosting loyalty.

So the question is: how can marketers ensure their communications strategies live up to the requirements of a seamless and consumer-centric post-channel age?

What the new world looks like

The idea of an integrated consumer experience isn’t new, but until now typical campaigns have viewed each touchpoint as a progressive step in a journey that still flows through the traditional purchase funnel. In the post-channel world the traditional funnel no longer exists. The route individuals take follows the path of their choice, which means marketers must build seamless campaigns capable of accommodating their needs. How and where a consumer has chosen to interact with a brand doesn’t really matter; effective marketing is now about providing a cohesive and unique experience, regardless of touchpoint, at the right moment and in the right place. It is not enough for retailers to ensure shoppers are delighted in store, for instance, they also need to deliver positive interactions online to keep the consumer happy.

Marketing has come a long way since the days when each channel had its own campaign, but in categorising communication methods such as digital, in-store, social, and mobile as separate entities, the industry is still restricting itself to thinking, and often by extension, operating in silos. It is vital for marketers to break down the barriers to unification by creating a holistic picture of consumer activity using a combination of unified, holistic data and smart tech that takes them from “multi-channel” to “omnichannel”.

How can this be achieved? By following these four steps:

Step 1: Take an integrated data approach: As connected devices become more commonplace, myriad new solutions have emerged to help marketers collate, sort, filter, segment and analyse data from every channel, yet most operate independently – whether in different tools or managed by different departments – leaving marketers with multiple streams of disconnected audience information.

Marketers require interoperable solutions that can integrate a range of consumer data types from numerous sources and create a centralised, actionable view of the consumer. Armed with this data, they can adjust campaign messaging and targeting to align with fluctuations in audience needs, interests, preferences and purchase states.

Step 2: Use unified data for holistic execution: If the first step is to integrate data, the second must be to use that integrated data in a single omnichannel platform to allow integrated execution and seamless workflow across all addressable channels. The post-channel world requires holistic, coordinated, efficient media buying and optimisation, enabling the brand to move fluidly throughout the digital universe to engage consumers wherever (and whenever) they are. It is also important to recognise that cookies – the standard bearer of digital targeting and measurement – are not equal to consumers (think cookie deletion, environments where cookies don’t exist, like apps; cross device usage and more).

It’s critical to couple an identity management system that resolves to the individual level with your omnichannel execution. A system that can manage an all-encompassing media strategy within a single user interface, delivering integrated workflows, execution, and reporting across all channels with a foundation of identity as the consumer level becomes a must in a post-channel world.

Step 3: Incorporate machine learning and predictive analytics: Using integrated data, coupled with omnichannel execution, marketers can instantly identify pockets of strong performance, areas for improvement, and patterns in user behaviour that they can draw upon to enhance future messaging and delivery. But that’s not all. Platforms with self-optimising capabilities can also build a comprehensive view of each consumer that – over time – allows them to predict what those consumers are likely to want and when.

Armed with this information, marketers can run personalised campaigns that reach consumers at the most opportune moment and feature items of real interest. Using an omnichannel platform enables machine-based learning across addressable channels allowing marketers to optimise more intelligently, in line with their business goals, at the consumer level.

Step 4: Adopt cross-channel attribution: Most marketers understand that last-touch measurement approaches are suboptimal: consumers don’t simply make a purchase decision as a result of a single interaction, such as seeing a paid search ad. And yet, few have adopted an effective solution to this problem. Lack of executive buy-in, confusion over methodology, and lack of actionable insights are all common challenges marketers cite.

Yet in the post-channel world the organisations who want to win long term must embrace a multi-faceted attribution model with the capacity to track activity on a variety of channels and combine the resulting insight to produce a cohesive understanding of performance. This leads to better budgeting decisions, smarter messaging strategies, better performance, and happier consumers.

In an industry characterised by constant progression, it should come as no surprise that a new trend begins to emerge just as marketers are adjusting to yesterday’s innovation. As we enter the post-channel world a shift in perception and a move towards a more holistic viewpoint – of the consumer, first, and how a company re-orients itself around the consumer – is required for long term health. By following the four steps of data integration, holistic execution, machine learning and cross-channel attribution, marketers will find they will begin to tear down the silos by ensuring the experiences they provide are fit for the new world.

– by Joanna O’Connell

Why we need to use tech to amplify human ambition – rather than turn it off

Stop me if you are still in helplessly in love with the culture and practices of 80s adland, but there’s an inherent decadence in the agency sector these days, as technology surges on and humans lag behind. And it’s not helping anyone.

You can see it on the media side, where so many seem to switch on the tech and go to lunch, not worrying about the detail, because it’s all clever stuff and if it doesn’t get the job done, the offline media probably will. That’s the seductive peril of lazy media: technology has become more accessible, more connectable and spread across more media channels than ever before, and the reaction of many is simply to sit back and let it run on autopilot.

You can see it on the creative side too, where much of the ad world’s most expensive talents sit around writing big telly ads that hardly anyone is going to notice. Whilst ignoring the creative opportunities of many formats with just as much – maybe more – potential – the banners, the specific copy, the data-driven creative and formats – because it’s all a bit “downstream”.

Media has changed, and so has the creative it requires, but the industry isn’t changing fast enough to capitalise. Tools and automation should amplify human ambition, not replace it. Technology should make us sit forward, not back, bringing us closer to our audiences and the market, enabling us to think faster and move faster to help our businesses compete.

If they’re going to compete, of course brands must select, connect and manage their data and technology to surface insights, execute against them and measure the result. But we believe that ultimately, it’s still human ingenuity that provides the real sustainable advantage. And too much of that ingenuity is rising to the wrong challenges and fighting the wrong fights.

At a recent conference there was a particular lamentation about ‘the death of the billboard’. Meanwhile, someone said ‘my son makes about 20 memes a day, and at least ten of them have more of an impact than most of your billboard creative.’ There is plenty of creativity outside the great creative shops, and it is fast, furious and knows its market.

There will always be a need for the kind of creative that requires a longer gestation period. Bigger ideas do take time to percolate through. But a fast world needs fast creative too. And if you’re missing that, then you’re missing a large opportunity and probably a lot of your audience, too.

Smart clients have for years been trying to get their creative and media agencies to work more closely together. But they need more than that – they need a creative message that’s built for the different media opportunities and how that media is being targeted.

As long as creative teams are removed from the wider media landscape, with its technology, its targeting capabilities and its rich market insights, they will fail to do their job right. Creative that is developed without a granular knowledge of the media targeting options is doing half the job, at best. At worst, they will completely miss the point.

The more native the creative, the better it works. The more your Snapchat work looks like great Snapchat content, the better it will perform. Your telly ad squished into that, or a skyscraper banner format, on the whole, probably won’t

Perhaps the answer is to follow the example of John Caples, a naval engineer turned creative who now lends his name to some prestigious awards. At BBDO from the late-1920s, he pioneered ad-testing, constantly measuring creative against its results. Tweaking, tinkering, combining. But continually sensitive to the place in which the ad appears, obsessed by the results, and forensic about which aspects worked, what didn’t and why.

Perhaps the answer in this tech-rich age is to get some really old-school ambition.

– by Dan Thwaites

Marketing machines still need a human touch

Earlier this year Google rolled out a new ads settings feature that allows users to mute ‘reminder ads’; known in the wider digital industry as retargeting ads.

But why would consumers want to make use of this feature? When managed effectively, retargeting ads should improve the user experience, reminding them about products they have browsed, suggesting viable alternatives, delivering relevant special offers, and otherwise building a relationship between the consumer and the brand. With 92% of consumers not ready to purchase on their first visit, retargeting is a vital marketing tool and is highly effective at encouraging action, be that a purchase or a newsletter sign-up.

The truth is some marketers have relied too heavily on machine learning (ML) algorithms that drive retargeting, forgetting that – while ML is an incredibly powerful development within digital marketing – effective campaign management will always need human involvement.

So, let’s take a closer look at how machine learning is used in retargeting and other types of digital marketing and explore why the human element is still so important.

Programmatic: enabling individual understanding

Programmatic media buying is one of the key areas of digital advertising to benefit the automated nature of machines. Using vast amounts of data, it allows users to be reached at scale, and with just milliseconds to bid on an impression, ML can crunch the data and determine the investment that can be made on that ad placement.

Traditionally programmatic targets cluster audiences or groups with similar traits or interests, but with the introduction of ML it can now specifically target individuals according to their unique profile and preferences. Using predictive analytics allows for a better understanding of the consumer and delivers personalised, relevant messaging to meet their real-time needs and strengthen the brand relationship.

But using ML in programmatic isn’t as simple as pressing a button and letting the technology do the work. It is only as good as the algorithms upon which it runs, and the data used to feed it. The human touch is necessary to develop and adjust these calculations, as well as to decide on the most appropriate data streams to feed them. The real-time insights available for analysis are broad, from demographic, psychographic, and location data to browsing habits and purchase history – and human intelligence is necessary to determine which combination of points will drive the required outcomes.

As programmatic ads are served to real people, the human touch is also necessary to factor in the elements of behaviour that machines may never fully understand.

DCO: delivering the most engaging creative

While programmatic reaches the right consumer at the right time, dynamic creative optimisation (DCO) allows the served ad to be specifically tailored to the individual. By combining the most appropriate elements such as images, backgrounds, and calls to action, DCO utilises ML to adapt messaging in real-time, based on various data points including a user’s location, interests, and demographic. The context of the creative can also be customised dependent on the consumer’s position in the path to purchase, such as delivering a brand ad to a new prospect to drive awareness, or a retargeting ad to a previous website visitor to encourage a purchase.

But while DCO can effectively compile ad creative specifically tailored to the individual, humans are still required to design elements with great aesthetics and to determine the level of personalisation consumers will find engaging rather than intrusive. They also need to link DCO technology with relevant systems such as inventory logs to ensure users aren’t being targeted with products that are out of stock or offers that are no longer valid.

Machine learning is revolutionising the digital marketing landscape, making it possible to predict an individual’s real-time needs and deliver the best message at the right moment to meet those needs, but it still requires the human touch. From brand awareness to retargeting, a bespoke, hands-on approach to campaign management is the ideal way to get the best out of the unison of human and machine.

– by Piero Pavone

Are below the fold ads more engaging?

Conventional wisdom would say that an ad that is above the fold would be more effective than one that a user won’t see unless they actively scroll down the page. New research from ad tech company Sovrn seems to suggest that the opposite may actually be true.

The company looked at over three billion engagements across 130 million page views on 400 websites to see whether ads above or below the fold into which bring the best results.

The research team focused on the difference between engagement time, which is the total time that a page is open and the user is deemed active, and dwell time, which is the time between the user loading the page and leaving it by closing the window or clicking another link.

The results seem to show that ads below the fold were more engaging than those above it. When it came to dwell time, users were engaged with ads below the fold for 27% of the viewable dwell time. This is compared to just 3% for ads above the fold.

Ads below the fold are also seen for 2.6 times longer than those above it, potentially meaning higher levels of engagement. Ads above the fold are currently up to five times more expensive than their bottom dwelling cousins, so brands choosing to focus below the fold may be netting themselves a great deal.

Dwelling and engagement

“Currently the industry prioritises viewability, or dwell time as a metric, but our research has highlighted that this is leading advertisers to make potentially costly decisions about their audience,” Andy Evans, CMO at Sovrn comments.

“We’re all guilty of opening browser tabs to look at content that we end up closing without even seeing the page, let alone an ad, and yet current metrics could end up counting these such instances, when they shouldn’t. By looking actively at engagement and various factors such as a click, scroll or tab changes, we can see that the user is engaged and increase the propensity to convert by targeting them in that moment.”

An important element when considering ad placement is also scroll depth, which varies significantly by device. The exit point for users on mobile tends to be halfway through the content (54%), a third of the way down the page on tablet (38%) and a quarter of the way down on desktop (23%).

– by Aaron Bob

Podcasts reeled in $314m in ad spend last year, finds IAB

Popularised by titles such as Serial, Stuff You Should Know and Ted Radio Hour, the humble podcast raked in $314m (£235m) in ad spend throughout 2017 in the US, according to new research by the Interactive Advertising Bureau (IAB) and PwC US.

That’s an 86% hike on 2016, while the study forecasts revenues on the channel to hit $659 million by 2020.

Of the self-reported data provided by top podcast companies in the study – including Audioboom, How Stuff Works and ESPN Radio – revenue for 2017 sat at $257m (£192), representing a 117% increase from $119m (£89m) in 2016.

Host-read and ‘baked-in’

For two-thirds of ads in 2017, it was host-read ads that were the preferred format for advertisers, the majority bought on a direct response, cost-per-thousand basis (64%), followed by brand awareness ads, among 29%.

In addition, ads integrated or ‘baked-in’ to podcasts were the most popular type of ad delivered in 2017, rising from 44% to 58% year on year.

Of the 14 podcasts measured in the study, just four accounted for more than half of all advertising revenue in 2017, shared across Arts/Entertainment (17%), Technology (15%), News/Politics/Current Events (13%) and Business (11%).

Who’s buying?

When it comes to the types of advertisers buying placements within podcasts, the IAB found that financial services spend the biggest, taking an 18% share, while direct-to-consumer retailers and arts & entertainment brands represented 16% and 13%.

Commenting, the IAB’s executive vice president of industry initiatives, Anna Bager, said that advertisers are increasingly recognising podcasts as a “powerful platform” to reach and engage with a captive audience.

Meanwhile, PwC US partner, David Silverman, added; “The growing trend toward ‘anywhere and everywhere’ media engagement has created a tremendous opportunity for digital media, of which podcasting is a significant component.

“Whether at home on a smart speaker, at work on a PC, or somewhere in between on a mobile device, more and more Americans are listening while they live, providing a robust podcast platform where advertisers can connect with today’s consumers.”

– by Mark Jones

Norwegian CMS startup Sanity wants to kick content creation out of the 90s

As a digital marketer, you’ve more than likely to have had a run-in with a content management system (CMS). If you’re lucky, you might even get to use one every day.

Whether it’s WordPress, SilverStripe, Drupal or Django, tucked away in the backend, it’s easy to take these painfully functional workhorses for granted, but one Scandinavian startup thinks the status quo is well overdue for an overhaul.

Sanity is the product of Norwegian digital agency Bengler and co-founders Øyvind Rostad, Simen Svale Skogsrud, and Even Westvang, who want to build a CMS native to the connected world its forebears were never designed for.

“Most people working today don’t even want to think about their CMS systems,” said Westvang, Sanity’s CPO, to Business Insider Nordic; “I think it’s obvious that existing solutions [have] been stuck in the late 90’s for many years.”

The idea for Sanity stemmed from its founders’ own “personal discomfort” with CMS, who found the most common platforms were time-consuming, and ultimately, no longer fit for purpose in a digital ecosystem built on seamless connections between website, smartphones, social media and video.

Sanity is trying to eliminate a reliance on page structure as the governing principle of content creation. The product acts to centralise all content within businesses while taking into account new technologies and platforms, and also caters for real-time edits to the same content across numerous sources.

“For many companies, the website becomes the primary source of truth on what they’re doing,” said Skogsrud; “What you should do is structure your content around what your company actually tries to achieve – the projects, the people and the clients – and get rid of the page as the organising principle.”

Enabling for real-time content collaboration across teams, Sanity stores content in one database, allowing for distribution via integrated APIs to smartphones, web pages, or even brochures or coffee tables books – the key point being, that where the content ends up should not need to be predefined.

According to BI, the idea came about at Bengler when working for client OMA, a Dutch architect. Using one data source, a combination of “architectural images, presentations, books, crediting and timelines”, the team were able to create a website, business development tools and print-ready portfolios.

“Working with structured data let us unlock achievements like looking up their buildings on Instagram over APIs and adding a content curation interface to the CMS to allow adding them into the data repository, and onto the website,” explained COO Øyvind Rostad.

“Along with external news sources and their own activity we created a real-time narrative of how their works are being used.”

Backed by a suite of clever features and integrations, what Sanity really gifts to the market is a refreshed (and well overdue) perspective on content creation and its place within branding strategy and communications.

It’s not a stretch to imagine forward-thinking agencies adopting Sanity for their clients. At the same time, however, it’s also easy to imagine that many companies will be reluctant to kick their old addiction to the archaic.

Sanity is now looking to expand what it hopes to be a “category-defining” offering following a $1.1m (£880k) seed round from tech investors and founders in its home market, with sights set on San Francisco.

– by Mark Jones

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