What will programmatic look like in 2027?

2017 saw the tenth anniversary of programmatic advertising. From its humble beginnings, over half of all non-search digital ad spend is now made using the technology. The days of slow deals, subject to human errors and inefficiencies, are increasingly behind us.

But adtech’s story is far from over.

The next ten years will see new technologies that will fundamentally change the way advertising is experienced in our day-to-day lives, whether as media buyers or as consumers. It is our responsibility as technology providers to capitalise on these changes as best as possible, delivering what is becoming a genuinely helpful service by connecting consumers to the purchases they want to make.

By 2027, programmatic will become ubiquitous in the marketing sector. It will no longer be a line item on a media plan, but will be taken as a given by media buyers. Programmatic will extend its depth, moving into more channels such as DOOH, TV, Radio, and VR. It will also extend its breadth to more consumers, yielding more data across more localities to properly optimise successful campaigns.

Ditching siloed channels

Understanding the omnichannel user experience is already a must for any effective programmatic marketer. The way an ad is engaged with by a consumer, between, say, their desktop and mobile, is crucial for advertisers to understand to best optimise their campaigns. The ‘single view of the consumer’ across multiple devices currently spoken of will be a well-established state of affairs, with marketers having an accurate view of cross-device behaviour.

The way consumers engage with multiple channels will change too. A search for a product or service on their smartphone will instantaneously update the ads recommended to them when on their laptop or tablet. What’s more is that consumers will quickly raise their own expectations in light of these developments, demanding convenient, real-time offers and messages, and scrutinising ads which are irrelevant and unnecessary. The consumer will even start to see advertising as a core component of shopping, with smart refrigerators reminding them of the need to buy milk through an ad, having detected that they don’t have any.

By 2027, omnichannel marketing will have reached new heights as we increasingly inhabit a computerised world. Developments in VR are but one example of the direction of travel, not to mention the growing market in tech-enabled wearables.

The adoption of programmatic trading by out-of-home platforms such as billboards are another sign of things to come. This computerised environment will be all the more reason for marketers to ditch increasingly outmoded siloed channel strategies, with specific channel budgets giving way to unified ones.

Just 6% of television ads will be traded programmatically in 2018, according to eMarketer.

But even that stalwart of traditional media buying will itself look radically different in 2027. As video-on-demand and streaming services blur the lines between TV and online video, traditional broadcasters will adopt the media buying techniques of their peers in the video universe.

Most TV ads, by 2027, will therefore be executed programmatically.


Current trends towards transparency in the media buying process will continue to accelerate. Marketers will exercise their right to know where exactly their spending is going, asking for guarantees that their content is running on quality sites alongside brand-safe content. Marketers will take a fully audience-first approach to media buying, matching high-value audiences to the best media in brand-safe contexts. Cast-iron guarantees that ads won’t run on brand-unsafe sites will become the norm, with the legitimacy of sites verified by the likes of Ads.txt.

The media agency will take on a new, more strategic role in this changing ecosystem, partly as a results of machine learning, which will automate several existing tasks.

Brand CMOs will increasingly look to their agencies to share the best approaches to media buying, data management and measurement – seeking their advice, for example, on how to best utilise their tech stacks, or in developing new joint products.

As the world of technology, data, and devices expands, the agency is set to take a consultative approach, delivering holistic strategy and bringing the latest innovations and approaches in marketing to their clients for consideration. Agencies will need to be on top of neatly summarising the story in a complex trove of data, which can be easily relayed back to the relevant CMO and to the board of a given client.

2027 is, of course, still a long time away, and making predictions of this nature are never a precise science. However, by looking at the fundamentals of where the industry is going, and where we’ve come from in such a short space of time, we can have an idea of where marketing is headed. It’s the job of any serious marketer to take these trends seriously and make the best use of them for their customers.

– by Emma Williams

How to be smarter with customer data audits

Each year, the data that marketing teams hold on their customers will degrade by around 10 – 20%. This is simply because approximately 1% of the population will die, 10% will move house, and email addresses and phone numbers will inevitably change.

Not all data will take the same amount of time to degrade. For example, details on customer segments, products or customer type will all deteriorate at different rates. The age of the data plays a part too. If it is over 3 years old then 30% of customers will have moved, so the entire database essentially changes address every 10 years.

It’s also not entirely equal. Data provided by existing customers may be more valuable to a business than that held against prospective customers, and this may vary between marketing campaigns.

With the General Data Protection Regulation (GDPR) coming into effect this May, it has never been more critical to keep data clean. Article 5 of the regulation states “every reasonable step…” must be taken to fix inaccurate data, but how can you know what to fix if you haven’t properly audited?

Here is how you can be smarter with customer data audits:

1.) Focus

Narrowing a data audit across either different products or customer types (such as active, lapsed, prospects etc.) gives a basis for comparing results. This means you also have grounds to justify investment from appropriate teams if needed.

Imagine letting a product manager know the address quality of the total customer base is 95%. They would probably consider that a good score, so no action needed. However, if you can use tangible proof to show that the specific product’s customer address score is just 80%, despite the 95% overall quality, you are in a stronger position to get the support and resources needed to look into why the product’s score is lower.

Focusing the audits enables marketing teams to benchmark internally across products and business areas, as well as spotting problems. If one set of individuals has purchased two different products, but there is a difference in the data quality, you are well placed to dig deeper into the issue.

Analysing other variables, such as contact data validation, opt-ins, field populations and distributions will provide a full perspective of the data. If the product manager sees there are email addresses against 50% of customers, for example, they may not realise if, say, only 60% are verified. In this instance, only 30 in every 100 customers might be valid, not 50 in 100 as originally assumed.

When comparing datasets of products, if some have more opt-in rates and a higher percentage of valid email addresses, it could be that something is wrong. There could be issues with the system that passes the data across, or perhaps the on-boarding or data capture processes aren’t working properly.

2.) Regularity is key

As a rule, the longer the time left between data cleanses the higher the cost will be, as more data will have degraded and will need to be fixed. It’s much better to be proactive than reactive, to avoid paying out higher costs.

You can use regular audits in the same way you would an exception report. If they are set up to automatically run they can fix and improve data quality when it drops below a certain level. For example, if the amount of invalid email addresses gets to 10% or telephone numbers drop below a 90% match.

This approach means the investment is frequent and regulated, so that a high level of data quality is self-maintained. When data quality is taken care of, it allows teams to focus on pending marketing campaigns, or elsewhere in the business that needs attention.

Frequent data audits are a vital way to monitor and repair any inaccurate data, and from May you could receive a fine under the GDPR of €20m or 4% of a business’s global revenue, whichever is greater. Regular data audits mean you are in control of your data.

3.) Maximise the value of the data

Auditing your data for its quality is a vital step, but it is just the start of understanding it fully. Other work needs to be done to get a holistic view, and the audit lays the groundwork for this.

A data quality audit will tell you that, say, 10% of telephone numbers are invalid, but a next step would be to conduct further investigation into this variable, to understand the distribution of values, and the formats used (e.g. +44, (01423), 1423 etc).

It may be that the field is inconsistent in how the telephone number is captured and stored and this can impact how much of the data can be actioned. Correcting the data at source to prevent more dirty data getting into your systems is extremely valuable. Equally, correcting data so it can be efficiently transferred across systems reduces the manipulation time analysts spend on correcting data.

Ultimately, a data audit is a great place to start. Coupled with a more comprehensive view of data variables, you can move towards a position of maximising the usage of your data, and maximising the returns on it, as well as ensuring you meet best practice and comply with GDPR.

– by Rob Frost

Establishing a progammatic mobile media buying solution: Perils, pitfalls and partnerships

Many advertisers are now looking to internalise their mobile media buying processes, and numerous companies are being set up to offer advertisers a media buying service in the programmatic space.

There are two possible routes here, as in any decision that involves using technology: buy or build your DSP. But firstly, let’s define what a DSP actually is.

Because DSP stands for “Demand Side Platform” it should be intrinsically associated with technology-based companies that allow media buyers to purchase ad placements via bids in ad exchanges’ real-time auctions.

However, many of today’s so-called DSPs don’t own a proprietary platform – and in some cases, they don’t own any technology at all. This is particularly the case in the mobile space, where programmatic technology was established more recently.

This causes considerable confusion for the ad-tech ecosystem. Any company positioned on the demand side of the ecosystem can call itself a DSP, independently of whether it owns a platform or not.

Advertisers therefore frequently assume they are going “direct” to the programmatic marketplace by using a “DSP” – but most would be very surprised if they realised how many players can be involved in the chain to providing marketplace access.

Building from scratch

Don´t get me wrong: if you want to be a player on the demand side, providing a media buying service to advertisers and agencies, it probably doesn´t make sense today to build your own technology from scratch, and your tech stack can offer a lot of value without being 100 per cent proprietary.

All I am saying is let´s call a spade a spade.

Many players are building valuable Media Buying Solutions, but the market is also full of examples that mirror the obscure world of traditional advertising, with never ending chains of Ad Networks working with each other as simple intermediaries – and calling every single player on the demand side a DSP just contributes to the confusion that allows these intermediaries to survive.

For those looking to establish a Media Buying Solution, it’s clear the choice of approach is a complex one, and the pros of one aproach are precisely the cons of the other.

The main advantage to building your own DSP from scratch is of course the fact that you gain full control over your offering. You own it, and as your needs change with time, your DSP will be able to adapt accordingly.

However, each of the components of the solution are fairly complex (in a constantly changing industry landscape), so if you decide to build entirely in house you need to be ready to invest in managing this complexity and its corresponding high costs on an ongoing basis.

It’s not just a one-time development. These are only some examples of basic things your in-house team will need to stay on top of, just for pure maintenance:

  • each particular connection to a supply partner has its specific idiosyncrasies and is constantly changing, with changes often affecting different ad formats in different ways
  • ad exchanges and publishers may change the rules of the game (e.g. the recent introduction of first price auctions or header bidding).
  • ongoing challenges around tackling Ad fraud

A DIY build may be your only option if you have a very specific need that no other technology out there can accommodate, of course. But make sure you do not underestimate what it takes. Building is rarely the challenge – it’s making it work effectively that’s the tricky part.

From a wider market perspective, the downside to building from scratch is that if we’re all reinventing the wheel, rather than innovating and refining demand offerings, no real progress can be made to develop the media buying ecosystem – We all end up competing against each other instead of standing on each other shoulders.

Now, you could say that the level of maturity in the market today should be enough for most companies to prefer building a Media Buying Solution through partnerships instead. Even in the mobile space, which poses its own set of technical challenges, it has been six years since the first mobile specialist DSPs were started.


Partnering means you can avoid dealing with low level elements that don’t offer differentiating value to your customers, freeing up time to focus on what makes your service offering unique.  There are enough partners out there with proprietary tech for this to be an option but you do, however, need to partner in a way that gives you enough control to provide that additional value.

Partner choice is key, because any partner that is an alternative to an in-house development must offer robust and effective technology, and advanced tools, whilst also offering you enough control to customise, differentiate yourself and add customer value.

This additional value can often be achieved by delivering a solution specifically targeted to certain segments of buyers, that can be tailored for the specific needs of that vertical, or offering enhanced value through innovative use of data.

Whilst working with a partner means you don’t have to deal with the details of the underlying elements that make effective programmatic media buying possible, those same granular elements might be crucial to differentiating your media buying solution from the many others out there – and this is the tricky part.

You need partners who can understand and cater to your needs (ie. if your audience is mobile, choose a mobile specialist), provide absolute transparency and granularity in reports and also equip you with the necessary level of control to differentiate your business.

They may be hard to find, but they are out there.

When adopting the partnership approach, it’s good practice to have two partners in place for the same element of your platform – firstly, as a ‘fail-safe’ mechanism and secondly to equip you with agility and the means to diversify.

In my view, as mobile DSP technology matures it will be those that partner well and build soutions  in a way that differentiates themselves from the masses that will rise to the top.

– by Noelia Amoedo

Imagery integral to the buying process for majority of consumers

According to an analysis of YouGov consumer data by martech company Pure360 shows that the importance of imagery when it comes to the purchasing process.

YouGov polled 2045 adults and found that 53% think that images grab their attention more than headlines. 61% expected marketing messages to include photos or images.

In fact, 62% of respondents said that they would not buy from a brand unless they can see the product being sold in its entirety. The choice of imagery is important too, with 54% saying that they prefer brands that use product imagery over those that use lifestyle images.

Komal Helyer, Marketing Director at Pure360 said:

“With image sharing platforms like Instagram growing in popularity, brands are paying special attention to the power of a picture in marketing efforts to attract customers. Thankfully today they benefit from a plethora of technologies to deliver more relevant, interactive, responsive and targeted images.”

Public image

The importance of brand imagery is likely to grow in the coming years. A recent eMarketer report estimates that Instagram will account for a third of all global social media users by 2021.

The price for using irrelevant or ‘bad’ imagery can be pronounced for brands. 69% of respondents said that it makes a brand look bad if they use the wrong kinds of images. For 18% there are also certain colours they prefer to see brands use and not using them can have a negative influence on their view of the brand.

But if the choice of imagery is done correctly, it can be a strong driver of brand advocacy. 23% of the consumers surveyed said that they like to share images of items from brands they like online.

“A great image alone may well not suffice in resonating with a potential or existing customer,” Helyer continued.

“Consumers are used to a personalised experience and if an image doesn’t fit with the text around it and isn’t relevant to them, it could potentially damage their propensity to make a purchase. On the other hand, our research has shown that a decent number of British shoppers will share a picture from a brand they like when the image is right.”

– by Colm Hebblethwaite

VR’s hidden secret: it’s a real-time content solution

The love affair between marketing and virtual reality (VR) has been blossoming for a fair few years now. So much so that these days it’s not uncommon to see VR included in a campaign brief.

Although VR may be high on the wishlist, not every brand can afford it. Or at least, that’s what they think. And yet VR is harbouring a salient but untapped secret: it can be used as a near-instantaneous content solution that, far from draining budgets, enhances long-term ROI.

For a seductive new channel that’s so tightly associated with vast budgets, this statement might seem to good to be true. But the truth is that once a brand has invested in its first VR experience, the initial outlay will pay dividends. How? By establishing – almost incidentally – a real time content pipeline that can create everything from apps to augmented reality (AR) for multiple departments within the same company, and all at the touch of a button.

Let me explain…

Time saver

Once assets have been digitized for a VR experience, the initial hard work is complete and these assets can go on to have a life beyond their original purpose. They become the foundations of a future-proofed content solution where everything is already in place to create multiple formats and versions of the original content further down the line.

This means that departments outside of marketing, from new product development to training via sales, can reap rewards from the upfront investment. But not only will they benefit financially; they will also benefit by gaining enhanced content. Imagine how much more engaging and effective training sessions or presentations would be if content were presented as powerfully immersive VR, rather than through a screen or pages.

Real-time data-driven content also has the added benefited of updating itself automatically, with users receiving a pushed notification alert. What could be simpler?

In addition to being an engagement-driving, company-wide and cost-saving initiative, this approach is also a significant time-saver: having a suite of ‘live’ digitized assets helps us shift from clunky linear workflows to real-time. That’s because VR experiences are heavily dependent on game engines: an amazing piece of software, long used by the video game industry, that renders content sequences in an instant. If it weren’t for game engines, video game players wouldn’t be able to control their avatars in real-time.

So, game engines are the magic ingredient that give VR experiences their real-time interactivity.

Getting started

Game engines are now so sophisticated that they’re capable of taking existing data assets and displaying them in near photo-real quality whilst simultaneously allowing users to interact with virtual products in real-time. Combine this with a powerfully immersive virtual world and you get a formidable tool for communicating brand stories and much, much more.

Many amongst you will at this point be thinking: “That’s all well and good, but how do I get started?”.

Fortunately, the answer is a lot simpler than most marketers think:

Brands often hold a library of useful but underused data; for example, computer-aided design (aka CAD), GIS or 3D product scans. We can use this existing and readily available data to create a VR experience’s building blocks by simply digitizing them into assets suited for real-time applications such as VR, AR and immersive apps.

When this approach is taken, it creates an unexpectedly low barrier to entry for VR, which begs the question: why is VR seen as a medium that’s exclusively suited to big established brands with their big established budgets? It seems rather undemocratic to me that only brands with vast resources can reap the amazing benefits that come from VR.

Digitized assets

Brand use of VR is, understandably, synonymous with a marketer’s two biggest goals: entertainment and engagement. But that doesn’t mean we should ignore VR’s more functional potential. Once there is more awareness around the fact that digitized assets can be combined with a VR game engine to create a myriad of content in a near-instant, marketers from brands of all shapes and sizes will be able to make a more convincing case for VR.

They will also be credited with developing an initiative that unlocks the industry’s much-talked-about-but-little-delivered imperative of digital transformation.

In an era when brands need to be ‘always-on’ whilst serving up endless personalization-driven multiple versioning, VR’s use as an automatically updated, real-time and cost-effective content solution becomes utterly compelling. And the ramifications could go far:

VR’s use as a content solution poses a threat to the conventional but highly inefficient model where brands commission agencies to create individual pieces of content. Once brand-world wakes up to VR’s secret functional side, they may feel so empowered by creating their own engaging content at speed and at cost, that agencies will feel the pinch.

– by Mark Miles

GDPR and blockchain: the next stages in programmatic advertising’s evolution?

This year has been one of vast technological development across the ad tech industry. Emerging technologies such as Artificial Intelligence (AI) and Machine Learning have continued to establish themselves as key drivers of intelligent advertising and personalisation across the programmatic ecosystem.

Meanwhile, Blockchain technology has rapidly increased its presence across the sector and is now presenting advertisers with a host of new ways to both diversify and secure their platforms as they look ahead towards the next 12 months.

Progression of programmatic

The new year is also set to herald a new era of evolution for programmatic advertising technology.

Recognised by advertisers for its unprecedented ability to streamline the process of ad buying for advertisers worldwide, programmatic technology is now firmly positioned at the forefront of automated and data-driven decision making for advertisers, so much so that it is now predicted to account for 100% of all advertising trading execution by 2020.

Advertisers are not only embracing programmatic solutions to improve the efficiency of their ad spend; many are now also using the technology to address industry wide challenges, such as fraud, ad blocking and a lack of transparency.

Yet, a new year has begun and new technologies continue innovating, the once aggressive progression of programmatic advertising is beginning to decelerate. While it is still expected to grow at an average of 28% in 2018, hitting US$ 64bn globally, this rate is much slower than what we have seen in the last few years.

This is a likely sign of the technology entering a new stage of increased maturity, as it continues to prove its value within the sector.

GDPR and its impact on programmatic intelligence

The evolution of programmatic advertising technology will not only be impacted by its own loss of momentum. The forthcoming introduction of the European Union’s General Data Protection Regulation (GDPR) in May is set to transform the way programmatic advertisers both collect and process the personal data of consumers. Once enforced, GDPR will require programmatic advertisers to be more transparent by obtaining active consent from customers for the use of their personal information, and will also give consumers the power to remove their accumulated historical data from any database they wish.

Yet, with today’s programmatic advertising technology so inherently reliant on consumer data to provide intelligent and automated ad targeting, these unavoidable regulation changes may well undo much of the progress made in enabling automated and personalised advertising, which has been largely generated by the rise of the AI trend in recent years.

This machine-led technology is currently used by programmatic advertisers to collect smart data on consumers and tailor their messages accordingly and has been an asset to the programmatic ecosystem of late. However, the implications of GDPR could somewhat restrict the extent of the role that AI-driven technology plays across the sector in the future. This will create significant challenges for the innovation of programmatic advertising and could deputise its ability to offer advertisers an effective ad buying process.

With this in mind, I believe that today’s programmatic advertising technology can simply no longer provide brands with the level of both automation and transparency now required for success in the sector.

Coupled with ever growing concerns over fraud and transparency, it is now important that programmatic service providers welcome the potential of other emerging technologies, which possess the capabilities needed to address the aims of GDPR and ensure both secure and efficient advertising, to continue advancing throughout 2018.

Utilising Blockchain to enhance programmatic

One emerging technology that will undoubtedly have a significant impact on programmatic advertising in 2018 is blockchain. The technology itself has garnered many column inches across many industries since its conception a few years ago, and the ad tech sector is no exception. The nature of the technology can undoubtedly provide some obvious benefits for advertisers adopting programmatic strategies.

Its ability to create an immutable record of transactions and provide users with a full audit trail of every transaction makes it an instrumental asset to increasing security. By providing advertisers with an irrevocable receipt of transactions, blockchain can work to reduce or even eradicate the risk of ad fraud. What’s more, it also increases transparency over expenditure, by enabling advertisers to see exactly where their budget is being spent and exactly who they are transacting with.

With blockchain able to drive security and reduce concerns amongst advertisers over issues such as ad fraud and transparency, advertisers themselves will be able to devote more time to increasing the efficiency of their audience targeting and improving the personalisation of their advertising strategies. As more come to realise its benefits, it is likely that we will see a rise in the integration of blockchain within automated ad buying processes in the coming months.

As the digital advertising industry continues to strive for both successful automation and creativity in equal measure, it is vital that programmatic embraces the capabilities of new technologies to continue its innovation over the coming months.

Yet, with GDPR bringing new challenges surrounding the handling of consumer data and with the growing concerns over transparency and fraud still plaguing the industry, programmatic advertising as we know it will have to undergo a huge transformation to both evolve and remain dominant in the year ahead.

– by Zheng Zhang

The perfect partnership: when AI and machine learning meet marketing

Marketers have found themselves in an industry that’s always on its toes. There are more social media platforms than ever before. And, while they might present more opportunities to reach your audience, they also mean a lot of other voices to compete with. It’s never been such a flooded market to get a voice across in.

On top of that, consumers understand tech more than ever before. They know when they’re being marketed to, but will only tolerate that marketing if the subject matter and content is timely to their current place in a purchasing cycle or relevant to them. Sounds like a lot to handle, doesn’t it? Well that’s just every day for those in the marketing industry. A campaign will only work if it’s tailored to the right person at the right time and on the right platform.

Imagine conducting that outreach manually. Most marketers have thousands, if not millions, of individuals in their CRM systems. As well as an email account to contact them on, each of those individuals will, on average, have 5.54 social media accounts.

That’s a lot of data to analyse on a lot of people and a lot of places to be manually tailoring content and sending it out to. It’s a struggle to comprehend how it can be done without taking up hours of a marketing team’s day – or without human error.

Right platform, right message

Given there are so many channels to reach consumers, it has reached the stage where human marketers are incapable of analysing data themselves to completely profile their own digital or social media sentiment manually, let alone that of customers – even attempting to get close to it by physically setting up different campaigns to target each of their different audiences is extremely time-consuming.

A whole marketing function could spend innumerable hours drilling down and analysing data to create customer profiles, before taking even more time setting up the latest campaigns to go out across different platforms to reach different audiences. And, in such a fast-paced industry, letting things delay by even a minute likely means you’re late to the party and miss out. Furthermore, and perhaps most importantly, consider how that time can be better spent – with the team actually focusing on developing creative, head-above-the-parapet content to send to consumers and get their attention, rather than dedicating man hours on the grunt work of sending basic messages out.

So, what’s the answer?

Well, this is where marketers need a platform or a program that can conduct data analytics with added machine learning and artificial intelligence to support their campaigns. For any marketer serious about driving interactions with their audiences cross-platform, AI and machine learning is a dream come true. Marketers need a solution that will tap into their existing audience data for them and analyse it. Then they need to bring in the latest digital and social media activities of those customers to ensure it’s building a ‘single view of the truth’ based on the latest market and brand insight – all in real-time. That’s half of the job done. But, the true beauty of AI and machine learning isn’t just in the analysis, it’s in the execution.

A program run with AI and machine learning can automatically work out which of your current marketing messages need to go to which audience – and on which social or digital platform. All with as much intervention as the marketer deems appropriate. Both AI and machine learning take the profiles and uses it to take care of personalisation – and with content tailored to their preferences and previous behaviours. In such a complex, saturated marketplace, we’ve hit a point where an AI/machine learning program is the only way to be running that outreach at scale.

Marketers have a lot on their plate to get the job done. Right people, right time, right platform, right message – and all at scale? That’s far more than a marketer can hope to achieve manually. But, getting AI and machine learning on-board in their marketing outreach can do the job and more – making sure consumers are getting the personalised content they require to interact with the brand.

– by Akhilesh Ayer

Is current digital ad research adequate?

Only 5% of media and marketing professionals currently believe that the commercial research studies on digital advertising are of good enough quality.

The data, from a survey of 220 industry professionals carried out by Inskin Media, found that 57% thought that the commercial needs of the company owning the research is the biggest obstacle to the production of useful content.

23% reported that most of the time they disregard commercial research projects, with 19% considering the majority of them to be absolutely useless to them.

Perhaps unsurprisingly, it is research agencies were regarded as producing the highest quality research content, while media buyers and media sellers were regarded as producing the worst kind of content.

“The industry has been deluged by studies on digital advertising over the last decade, most of which is used as a Trojan horse to promote a sales agenda,” said Steve Doyle, Inskin Media’s CCO.

“Unfortunately, much of it isn’t fit for purpose and it’s tended to tar everyone with the same brush. Paradoxically, it’s also created the problem of undermining genuine findings even if the company doing the research has a commercial interest in proving them, so the results are mistakenly ignored.”

Doyle also added that he was well aware of the “irony of producing a research study saying research quality is inadequate”.

Explaining the method

So, what is the current acres of commercial research failing to do? 61% of the survey respondents say that quality and detail are the most important factors in making research good content. 54% cited relevance as the most important factor.

A couple of suggestions really resonated with respondents as methods to try and improve the quality of commercial research. 71% said an independent industry body ‘seal of approval’ would be useful, while 70% would like to see detailed methodology sections become standard.

“The rise of online survey platforms means anyone with a few hundred pounds can produce one but hopefully the industry will start demanding far more rigour and detail about the methodology, as well as taking into greater account the agenda of the company producing it,” says Doyle.

“Indeed, the support for an independent seal of approval is reminiscent of what’s happened in Germany. The major trade bodies along with Google and Facebook launched ‘Qualitätsinitiative Werbewirkungsforschung’ – an initiative to increase transparency and quality in advertising effectiveness research.”

The media and marketing professionals surveyed prefer to hear research insights in face-to-face presentations (56%), with infographics (45%) and trade magazines (37%). Of all the methods cited, webinars were the least popular with 14%.

– by Colm Hebblethwaite

How can gamification decrease the opportunity cost of onboarding?

Have you ever calculated the cost of an ineffective onboarding process? Or do you think that your company uses its potential to the fullest?

Let us imagine now a different situation. All newcomers are introduced to their workplace so well that they can carry out their tasks effectively right from the very beginning. Knowledge trainings produce sales representatives who offer high customer service right from the start. Employees know details about each product from the portfolio and represent the company and its mission in the best way possible. If the description above is not about your company, it is high time you considered introducing the employee gamification software.

Companies that focus on an effective employer branding strategy see some potential in engaging newcomers. That engagement, during their first days at work, may involve meeting the team and preparing the work equipment. But not only. Gamification may also be an interesting layer to knowledge or skills trainings needed to carry out all work duties in a proper way.

A smooth start in a new workplace

Meeting new staff members, preparing the work equipment, installing all needed programs or setting up an account in the main messaging tool used by the company. All these actions are simple but, without proper instructions, they may be stressful and take way more time than you would initially expect. However, by boosting the employee engagement we may turn those activities into an excellent step by step guide, appealing to our new employees. For this reason, we have come up with a ‘welcome game’. A small app where each new employee may enjoy learning all the information they need to start their work by playing games.

The result was nearly 100% of newcomers participating in the game and acclimatizing to their new workplace within the first week at work.

Gaining knowledge as an adventure

Do you use e-learning programs to train your future sales representatives? Or do they receive leaflets, catalogues or other materials to become familiar with your product portfolio or customer service tricks? What results do you get? One of our clients approached us to ask whether we saw a possibility to improve his current results in knowledge training by combining the educational content from e-learning platforms and marketing materials with engaging solutions to create a universal tool to encourage sales forces to improve their knowledge and skills by participating in a gamification scenario.

We implemented a gamification platform that pushes the content about client’s products, customer service and the brand. After adding the fun factor, entertaining storyline and a bit of rivalry, users visited our platform regularly and took as many actions as they could to discover the new content.

The more we know about the users of a gamified solution, the better we can inspire them to undertake specific actions like reading about new products and their competitive advantages.

In our project, we analyse users’ activity month by month and adjust our gamification mechanics to it. Our work brought the following results:

  • a 28% increase in the weekly frequency of visits owing to the introduction of a new feature – educational duels between users,
  • a 198% increase in the monthly number of openings of the educational content following the adjustment of task mechanics to the users’ preferences.

Information about your employees and their most effective ways of learning can be used to increase the performance of newcomers at work and to plan subsequent trainings aimed at developing their skills.

An opportunity cost of onboarding

Each employee engagement software may have various forms and be used to achieve different goals.

Gamification may have impact on simple tasks connected with starting work at a new company. It can also be a core of the knowledge training program. The right question to ask is not whether to introduce gamification, but what is your current opportunity cost connected with an ineffective onboarding – and how do you decrease that amount with engaging solutions?

Text prepared with cooperation from Comarch.

Brick and mortar still key to winning retail customer experience

87% of retail disrupters say that they believe in the benefits of physical stores and will continue to try and open them in the future. While much has been made about ecommerce’s continued chipping away at retail sales, many retail brands still think that a physical store is an important part of creating attractive experiences for customers.

The data comes from the 2018 Retail Disruptors Survey from JDA Software, who interviewed over 100 retailers worldwide. Disruptive brands are categorised as those, ecommerce-based and not, that provide high quality products and services, are faster and more responsive than their rivals and have “fundamentally changed the customer experience”.

And rather than abandoning bricks and mortar, disruptive retail brands see stores as an important part of the multi-channel approach. 71% of them believe that cross-channel fulfilment such as buy online, collect instore drives foot traffic into stores as they continue to grow in popularity.

60% also thought that loyalty programmes and interactive technology are also good ways of getting shoppers into stores.

“The results of this survey are clear: Disruptors are more willing to sacrifice a faster growth trajectory to achieve the customer experience shoppers expect, with a mix of human- and data-driven insights for the perfect blending of art and science,” said JoAnn Martin, vice president, retail industry strategy, JDA.

“Retail disruptors realize that technology is a strategic enabler and not just a cost to be managed. This will be absolutely critical to success in an evolving and turbulent time for retailers.”

Focus on experience

Two factors seem to be setting retail disrupters apart from their non-disruptive peers: a focus on customer experience and a willingness to invest in tech to help make it better.

“Disruptors are more willing to implement new technology to improve the customer experience, but they’re also quick to change course when they don’t see benefits they anticipated. And disruptors right-size to hone in on the right technology mix that yields the best shopping experience,” noted Martin.

The kind of investments that are working for disrupters include end-to-end supply chain visibility (49%), regional and localised distribution centres (38%), and partner collaboration with vendors (38%).

Investing in customer acquisition priority areas is another key part of creating the right kind of retail experiences. 58% focus on engaging lifestyle content, while 57% are investing in customer-focused events and activities.

“So, where do retailers go from here, especially if they want to be disruptors? They need to live and breathe the intersection between products and customers, finding the right balance between human- and data-driven insights. Deploying new technologies quickly – while also changing course if they aren’t working – will also be important to keep speed and agility top priority in order to support their stay ahead in an ever-changing retail landscape,” said Martin.

– by Colm Hebblethwaite

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Call Us 1-949-954-7769
eMail us at: wantmore@teamdebello.com