Advertising is on a roller-coaster ride in the 2020’es. As one of the first budgets to be affected in times of uncertainty, advertising took a dip at the start of the pandemic. It also picked up for new types of advertisers. Then the entire underlying data set for targeting based on user behaviour changed, as people’s financial situations changed, as their relation to touching products and going to shops degraded, and as ecommerce picked up. And then ecommerce boomed and digital advertising rose to new heights again.

And under the hood, things are changing too. Artificial intelligence is making inroads into advertising management, new privacy legislation changes the use of data. And the disappearance of third-party cookies is promising to send shockwaves through the adtech industry.

All the while, the major platforms, also known as the triopoly of digital advertising, Google, Facebook and Amazon continue to experience double-digit growth at 20-40-60%. Search engine advertising, at the core of the Google offering is still on a positive and growing trend. This is despite saturation of click prices in mature markets. And despite a halted growth in the basic market of search, as the majority of the worldwide population now has access to the internet.

But if the the number of searches performed by users – the search market – is not growing, and if click prices, the basic monetization of searches, can’t rise any higher, where is the search advertising journey going? For Amazon, search is still growing, for Bing, the CPCs may not yet have hit the ceiling, but Google might be close to maxing out on those two growth dimensions.  And so it is time to look inwards.

What Search Engine Advertising is today

Most search marketers who have been brought up with Google and Bing ads today agree that Amazon Sponsored Products should be considered as “paid search” too. But they can also get caught throwing display ads from the Google Display Network into the mix. Perhaps because those are still “pay per click”, or PPC, one of the other names search marketers often give to search engine advertising. Furthermore, the overlay of audience targeting which has arrived in search advertising engines in recent years is taking the focus away from the keyword.

Digital advertising is similar to financial investments today. You choose among a wide range of ad streams for which you try to predict future returns on the basis of past performance. Some are short term bets, others are long term. No outcome is ever guaranteed.

In the range of possible options, Search Engine Advertising represents a wide number of streams. Brand keywords, category keywords, automatic targeting, automated optimization and bidding, maximization of clicks or revenue or return on investment. Reliable and unfied tracking is key to succeeding.

But there are also some huge differences between financial investment and advertising. In finance, there is no hidden outcome, no organic growth, no retargeting pools, no brand effect and no synergy effects either. This is where advertising stops being scientific, it has a vast number of moving pieces which interact with each other.

What are the drivers of change in paid search?

For many years, search advertising was always the same: find the right keywords, write compelling ad copy, adjust bids for optimum visibility, send users to highly converting landing pages. It was spreadsheetable because the number of variables remained low.

Over time, however, more variables entered the equation: users morphed from desktop to smartphones, tablets and became multi-device users. The ads evolved with extensions and contextual elements to become multivariate entities with no fixed form or shape. And the audience targeting overlay made the number of variables explode. We explored all of these variables in our 2018 Search Trends report to conclude that something fundamental had changed.

Advertising engines started building optimization tools for managing this complexity. In Google, these tools are known as Smart Bidding. They take a wide range of variables into account, apply machine learning, and target one specific and measurable outcome. In the 2020ies, Smart bidding has become the norm rather than the exception. Search marketers are no longer testing between keywords, they are testing between algorithms.

Smart bidding is the arrival of artificial intelligence (AI) in ad optimization. But it is not the only thing happening. In our 2020 Digital Marketing Report, set in the context of COVID19, we identified radical changes in user behaviour, and disruption in the data as immediate effects of the sanitary crisis. But overlaying these trends, the penetration of AI, and the data challenges became apparent. Privacy legislation is changeing both user behaviour and tracking methods, and the large platforms are increasingly accumulating data and restricting marketers’ access to it. On top of AI, user behaviour and privacy legislation, we are also entering a user tracking paradigm shift as third-party cookies are being phased out and the concept of “cohorts” taking over.

6 inflexion points for PPC automation

Automation is what drove the industrial revolution, and it is also a major driver of the digital revolution we found ourselves amidst. So whenever a search engine suggests automation tools, does that mean you should use them? Let’s look at some good reasons for automating or not.

• SKAGS: “Single Keyword Ad Groups” were a thing. Some agencies even automated processes to build SKAGs in their client accounts. Where search advertising is going today, there are many cases in which SKAGs risk performing worse. Optimization algorithms pull in the opposite direction of the SKAG, as they take more variables into consideration.
• Smart campaigns: Google Ads has a highly automated campaign type known as the Smart campaign. It simplifies campaign creation down to the basics and requires no keyword research. For small operations with a clear goal and reliable tracking, this type of automation can create great results. Just don’t ask how it did it, as you will get very limited insights.
• Dynamic Search Ads (DSA): Enter a URL and let Google Ads find the keywords to target. Then hope to find some of them in search terms reports.
• Responsive Search Ads (RSA): Enter variations for titles and descptions and let Google Ads find the winning combination.
• Smart bidding: Various types of smart bidding exist with the common feature of using a wide range of variables to optimize a search campaign towards once precise goal. This includes bidding on branded keywords to generate more conversions.
• Google Data Studio, PowerBi: Automate reporting of your digital advertising campaigns into dashboards updated in real time.

For most of the items above, there can be a bit of a trade-off. Only the very last point on the list is a no-brainer: absolutely automate your reporting as much as humanly possible.

The challenge with automation is that it applies fast algorithms to sets of data. You need to be careful to provide the right data via reliable tracking and well-considered limits. If your tracking is not 100% reliable, automating campaigns will not work efficiently. If you leave the advertising engine define what data is included, you may see cannibalisation of other campaigns, of other channels.

Keep your eyes on the data and your foot on the accelerator

Search advertising is looking inward for growth. Its engines are aiming to monetize more of the search by using the data to its advantage.

Search advertising for small campaigns are easier to create than ever before. Search advertising for large campaigns is potentially more complex than before, as data access is becoming increasingly blurred, more algorithms are applied and targeting mechanism change. A good approach is to mix and match the various algorithms, and work actively on delimiting and providing the best data for your campaigns to work with.

Keep your eyes on the data and try to interpret it holistically across all your communication channels. Set your strategic goals and pin them down with the right KPIs, then use as much automation as you can to accelerate outcomes. Not quite the autopilot yet.

If you are interested in search trends and outlooks for digital marketing, you will find more in-depth analysis in our recent reports: “Major Trends in Paid Search”, “Paid Search Strategies”, “Marketing on Amazon” and “Digital Marketing in Uncertain Times”.

Paid Search exploded back in the 1990s and redistributed the roles in digital marketing. Incumbents had a hard time adopting this new type of performance marketing and legions of newcomers grew to take dominant positions in the market.

Fast forward to 2020 where Amazon Ads is exploding and where the new incumbents of paid search-dominated digital marketing advertising agencies are having a hard time adopting marketing on Amazon. Is there a new legion of newcomers coming to take power positions within digital marketing?

Back in 2018 when we researched the way leading teams in Paid Search operated, we noticed that they seemed to lag behind on adopting Amazon. Only about a third of the teams had any activity on Amazon at all whereas 80% of them were involved in Shopping campaigns.

Although we didn’t actually ask that question, we assume that 100% of them were present on Bing via Microsoft Advertising. According to our calculations, right around the same time, Amazon Ads overtook advertising on Bing and with the recently published figures for Amazon Ads and its’ growth of around 40%, Amazon Ads may already be twice the size of Bing in terms of advertising revenue.

So, what are the barriers to entry into marketing on Amazon for a Paid Search team? We tried to compare some of the dimensions of our 2018 research (“Major Trends in Paid Search”) on advanced search teams and our 2019 research (“Marketing on Amazon in 2020”) on advanced amazon marketing teams to look at some of the similarities and differences.

Comparing paid search teams to amazon marketing teams

To start with, let’s establish that they all agree on the importance of Data analysis. In both surveys, around 60% of respondents even had a dedicated data analysis role assigned to their projects. So far so good.

Process and change

On the aspect of the work process, there seems to be great differences and perhaps one of the biggest challenges for getting going on Amazon is the fact that it is a less structured process than for paid search. The advertising interface is younger and many describe it as something similar to an early version of Google Adwords. Marketers have multiple accesses to country accounts, merchant accounts and ad accounts to manage. Amazon Ads rolls out new functionalities and changes the way it functions at an amazing pace and it can be difficult to establish a firm process and automate it.

Paid search teams are in a more stable environment and our survey showed that they automate at a much higher degree than Amazon marketing teams. 25% of the automate anything they possible can and are building a sophisticated automation stack. They also have an established process for acquiring knowledge and adopting change: they work closely with Google and with Microsoft advertising. This is much more challenging for Amazon marketers. Agency teams on the Amazon side are more recent, less structured, change is frequent and marketers have adopted a philosophy of constant test and learn. There is a pattern in this: if you can build a structured process, you can automate, if the process constantly evolves, you must test and learn to keep building the process.

The work rhythm also seems to be different. Paid Search teams report monthly (50%), where 55% of Amazon teams report weekly or daily. Is it moving faster or does it simply require more frequent attention to stay or track?

Integration and attribution

As an extension to the process challenge, we believe we have identified an integration challenge: where paid-search teams are adopting an integrated approach, Amazon marketing teams are still very concentrated on a stand-alone Amazon marketing service.

Perhaps this strong focus on a single challenge is what also affects the attribution model used. Most digital marketers will agree that last-click attribution is not the best way to report on your digital marketing activities, yet 55% of our respondents used the last-click attribution model (as opposed to 14% in our paid search survey). It is clearly a result of Amazon marketing being sales-focused and placed at the end of the funnel, but perhaps it also reflects the industry being less mature than that of paid search

Marketing on Amazon is still in its early stages but the industry is growing wildly and maturing rapidly. This year will se many marketers addressing the Amazon opportunity for the first time. Beware of the pitfalls 😊

Frederick Vallaeys, author of this new book named: “Digital Marketing in an AI World: Futureproofing Your PPC Agency” paints a very detailed picture of how machine learning has emerged in Google Ads over time. He was involved in the early days of Adwords when Quality Score, the first machine-learning activity for ads, was first launched. Later, machine learning was used for early automated bidding solutions and for applying “broad match” to keywords and thus expanding the reach of an ad using fewer precise keywords.

Reading this part, it dawned on me how the work of PPC specialists is actually what the machine is feeding on. The more the digital marketers uses the tools, the better they get. “They” was referring to the machines. 

Back to the book, where Eric Schmidt has just entered the room at a Friday meeting in Google and has shared his vision for Google Ads in the future (today, as this was a few years back):

“a business should be able to come to Google, tell us their goals, write us a blank check, and then the system would just hand the rest”

This is an interesting direction to consider – Frederick calls it the “AI-first” direction – as that is clearly where Google are headed with the help of Moore’s law which is increasing computing power exponentially. In detail, this vision removes any handling of campaigns, of ad texts, of keywords, of targeting or of bidding.

He then goes on to explain how machine-learning models work. They learn on the data you input in order to build a predicted result. It is really great to get a look behind the scenes. The vision Frederick has on AI is that it will help digital marketers provide better results and can be a plug-and-play for anyone simply looking for “average results”. If you want more, you need to optimize the human-machine equation for maximum output.

Where does this take us in the future?

Parts II and III of the book go through the impact on agencies and people who work in PPC/SEA/SEM/paid search and maybe the wider digital marketing, even. There is a need for roles he calls Doctors, Pilots and Teachers. Doctors to diagnose the patient, Teachers to provide the right data to the AI and Pilots to steer campaigns in the right direction. Without having been into the details of these parts of the book, the wealth of insight it provides makes it a must for any digital marketing agency, and anyone working in this industry.

I interviewed Frederick for the Search Trends report while he was writing the book and his insights were a valuable contribution to it. He is practically giving his book away (the Kindle version) this week as you can get it for 1 dollar until Friday. I got it and so should you!

Available on Amazon: Digital Marketing in an AI World: Futureproofing Your PPC Agency

I was not involved in that project and suddenly felt very happy not to be. Maybe it was just a question of terminology, maybe something else was behind those words. You can’t remarket to something that hasn’t been marketed, can you?

Remarketing had become very popular indeed. Why was that again? Well because it generated “proven” conversions. It generated performance. Certainly not because of its (non-existent) capability to build brand awareness. This was of course before remarketing became really unpopular with users who felt stalked by cookie-fuelled remarketing ads for things they didn’t want or already bought.

Today marketers build advertising campaigns with a nuanced understanding of their audiences. They assume that each individual member of an audience will go through various stages on his/her journey towards the product or service we advocate. They can do detailed analysis of the end users’ characteristics in the shape of Personas and then try to understand in which way they can be touched and influenced in each of the phases they are going through.

The original user-journey mapping concept, the purchase funnel, originates from E. St. Elmo Lewis, who in 1898 described his AIDA model, which has four stages: awareness, interest, desire and action. This model was later adopted in the fields of marketing, sales and, more recently, ecommerce. The logic of the funnel is that you qualify and thus reduce your marketing scope when you pass from one stage to the next. This fits well with the measure-everything philosophy of digital marketing, where goal, transformation and tracking points can be established for each passage.

We used a simplified version of this model in our research for the Search Trends Report and it was clear that the most advanced players in the space we looked at, had a very broad scope of analysis for this. They considered it essential to understand this user-journey and most of them mapped their campaigns to the user journey in one way or another.

For a deeper look into how the most advanced paid search marketers consider understanding the user journey essential and look well beyond their main marketing channel in order to target users during their journey, you should read this article:  Where does paid search fit into the user journey? 

Early digital marketing was linear

When digital marketing first took off – as is the case for many marketing approaches – it was driven by strong converters. The most successful paid search campaigns 15 years ago were all trying to trigger an impulse buy and move along a straight line from which the user was not meant to deviate.

The set up would look like this:

1. find a “money keyword” (a keyword which indicates that the user who made the search query has a strong intent – a buying intent)
2. optimize a landing page with a view to immediate conversion
3. overbid everybody on the money keyword so you would harvest a maximum amount of visitors
4. split test the landing page to continuously improve its conversion rate

In the wild west of early paid search marketing, this approach made people rich. It also drove up competition and therefore auction prices and therefore made the search engines rich too. Those campaigns would be considered “performance” campaigns as everything was related to conversion: investment levels, remuneration of those involved.

And on the opposite side of the spectrum you would have the Brand campaigns. They would simply aim to position the brand in relation with the right queries or on the right websites. They would measure the number of impressions that were generated by their ads and would tie a lot more importance to being at the top of the page than to how many click-throughs that position generated, as there was no direct conversion on the destination site. A landing page could be a homepage.

Those two worlds – performance and brand – were very far from each other.

Digital marketing has come a long way since those early days. In performance campaigns, competition and cost increased, but so did targeting options and data availability, making the playing field more complex. Brand campaigns began to look at longer term value due to improvements in tracking and would start to synchronize with Performance-related activities.

State of the Art in 2019

When looking at hundreds of case studies we would have expected to see quite sophisticated set-ups for campaigns, but one of the things that struck us was that they rarely described more than 2 campaign phases. Two is of course a fundamental advancement compared to the former linear campaigns but with teams insisting on having in-depth understanding of the full user journey, it seemed simplistic still. The first phase would be essentially focused on Awareness (and/or Interest) and the second phase dedicated to Conversion. So where did that Consideration stage go?

In fact, it is hiding in there although it doesn’t have a dedicated campaign phase. All the communication that is being redirected at a Consideration-stage audience is usually tied together either with the preceding phase or the following phase. As an example, for Awareness campaigns, remarketing audiences will typically be addressed for consideration rather than directly for conversion. And in a conversion campaign, to broaden and qualify audiences, « inmarket » audiences will be used. These are covering our Consideration stage, so let’s have a look at a number of ways in which they appear in no particular order:

• Media partnerships
  Many large advertisers establish medium/long-term media partnerships. This allows them to have a continuous visibility and sometimes interactivity with a part of their consideration stage audience.
• Brand searches
  It is well known that searches with brand terms are among the most likely to convert. Brand searches are on the brink of conversion – sometimes the user will be an existing client (what’s their address, how do I log-in), sometimes they will be conversion audiences (let me find the website so I can buy the product) and then sometimes they will be in the consideration stage (on my list of alternatives I visit every brand to help me choose). It is useful to segment brand searchers by the use of customer match and remarketing audiences to identify those who are really in a consideration stage.
• Remarketing to derived audiences
  From an awareness campaign, it is sometimes possible to create derived audiences of those who have seen a video ad or those who have otherwise engaged or simply been exposed. These will be consideration stage audiences not yet ready to convert and in need of positive reminders of a brands existence.
• Inmarket audiences
  Due to increasing amounts of data and machine-learning algorithms applied to user data, it has become possible to define audiences which have a higher probability of Intent. This is very close to the definition of the Consideration stage. These Intent audiences are often labelled “inmarket” referring to a user being “in the market for …”. They are of course sector- and sub-sector specific.
• Prospect nurturing
  B2B digital marketing had a slow start compared to B2C. One of the reasons was that it becomes proportionally more difficult to track efficiently, the longer your sales cycle is and the more stakeholders are involved. And in B2B sales cycles are long and there are typically multiple stakeholders. One of the successful approaches used by B2B marketers is what is referred to as Inbound Marketing. It is a content-driven approach which aims to establish a relationship on the basis of an initial positive interaction and typically register an email address which enables for a process called “nurturing”. This process is typically mapped to a typical sales cycle and addresses the needs of the persona. This entire concept is clearly the materialization of a well-defined consideration stage.

In our research, it is still rare to see campaigns entirely mapped to a user journey. We believe the best possible strategic planning takes the route of audience research, persona building and user journey mapping and that doing this will become increasingly important and also increasingly mainstream as the number of variables in the digital marketing equation continues to increase.

We have, however, come a very long way since the initial duality of Performance on one hand and Brand on the other. Most advertisers are trying to build their path down from Awareness or up from Conversion to try to guide the user at every stage towards their offering. And excellent marketers also think beyond conversion as new opportunities in loyalty and advocacy are arising.

If anything like that were really happening then privacy has indeed died away and we are living in a world surrended by GAFA Big brothers. But it would be simple wouldn’t it? Google, Amazon, Apple, Microsoft all activating the speaker on your phone, transferring the data to a machine-learning data center, recognizing the speech and then words and topics. They know how to do all of this and could therefore use this data treatment to put you on an “inmarket” list of hot prospects for products related to the topics you were just discussing with your friends. Once you are on the “inmarket” list of profiles, advertisers will automatically target you.

Naa, this is too creepy.

As far as we know, none of this is happening although it makes for a good story. It goes hand in hand with the email you just got from a “hacker” who knows everything about you and who has registered a video of you while you were watching porn and is ready to release it to all your friends on social networks. That is of course even more creepy and even more a made up story. I believe you are safe for now.

Voice search is receiving a lot of attention in 2019, especially from the SEO community and because of the “Position Zero” in Google results, the one where Google shows content they scraped from your page – featured snippets – to give an answer to the users’ query without having to do one of those cumbersome clicks everybody tries to get from Google. This creates a rise in what Rand Fishkin nailed as “zero click searches” in this article.

But how important is voice search really? As always there is a lot of hype and when you look for statistics you mainly run into a Comscore prediction which nobody seems to be able to place. Voice search will NOT represent 50% of searches by 2020, please! Thanks, Econsultancy for putting that right.

We also did not find the source for “40% of adults perform a voice search per day”. Looking through sources, there are some circular references, and mostly survey results or predictions but no actual usage statistics. We are therefore making the following prediction:

2019-2024 is going to be the year of Voice Search
(like 2010-2015 was the year of Mobile)

In our survey of leading paid search teams for the Search Trends report, we naturally asked questions about the use of Voice search. What do you know, perhaps there is value in mining voice search queries to better understand the end-user journey and intent? Very disappointingly hardly anybody cared about voice search as seen in the illustration – and they are of course right. The main usage of the concept of voice search seemed to be in the keyword research phase.

Advertising in Voice Search

There is not yet an advertising interface for voice search. It looks like the monetisation by search engines is based on the device – Microsoft use Cortana to sell Windows, Google use voice search to sell Android phones and Google Home, Apple use Siri to sell iPhones and Amazon is all about the Echo. Once they’ve sold those devices, however, how will they justify continued investment in this race for Gold? At one point they are likely to want to use advertising are they not?

Q: If Google searches are increasingly done by voice, they could be losing revenue from ads in other channels and we can’t have that, can we?

Ad: “The following answer is brought to you by Innovell, provider of Digital Marketing Insights.”

A: “No, we can’t have that, that is not the way Google works – Google really cares about revenue and is not famous for shooting itself in the foot”.

The above example is the “sponsored by” approach and it is one of various ways in which Voice search could be monetized. Historically, Search advertising was such a non-interruptive advertising model but we have learnt from Youtube advertising that there is no longer any anti-interruption philosophy in Google. They are happy to stop a video to give you advertising before it picks up again just like Facebook. Would they stop half way through the answer and put an audio-ad in, though?

We can only really see 5 options for monetizing voice search with advertising as illustrated in the voice-activated Answer Engine overview below:

a) Pre-roll

b) Screen-synch’ed

c) Paid answer

d) Post-roll

e) Data-driven

(No, we did not include interrupting the voice answer with an ad in the middle as an option.)

Elegant advertising

Shall we be noble for a moment? We love search marketing because it is such a smooth and un-interruptive model. We hate interruptive advertising as in stealing your attention away from something else. We also dislike option C) above – imagine that the answer itself is paid-for. You asked a question and you get an ad response. We are not convinced this would even work as a user experience and find it unlikely that this is approach would be adopted.

The easiest and most obvious solution would be the pre-roll. It is a proven model in online video, on TV and on the radio. “This answer was brought to you by….” Inserted before the answer itself. But from a user-interface perspective, voice search is being adopted because it is convenient and an ad pre-roll would really ruin that user experience.

In the area of elegant solutions, there would be ads on a synchronised screen. However, it would likely not be very effective as your attention will be on the voice answer. The most effective approach would be voice. Voice ads before or after the voice result – maybe after the search result would make sense?

Whichever advertising model finds it way into Voice search, there is actually a very good chance that voice search providers will want to use the data as well in the way we mentioned above. It may be the best way to monetize the searches.

Shall we let the creep in?

This post is based on an extract from the #searchtrendsreport found on https://www.innovell.com/major-trends-in-paid-search/ 

It is also written simultaneously with the podcast with Jason Barnard AnswerEngineOptimization (Search & Shopping – where are we going in Ads?)
https://kalicube.pro/podcast-series/search-y/ahjorth

After publication, this very relevant podcast was published on The Guardian, “Is Facebook spying on you”: https://www.theguardian.com/news/audio/2019/apr/08/is-facebook-spying-on-you

This survey claims 59% of users believe they have been retargeted with ads based on what they said via voice. https://www.signs.com/personalized-ads/

The Facebook point of view in this podcast: https://www.independent.co.uk/life-style/gadgets-and-tech/news/facebook-listening-listen-does-is-microphone-app-phone-mark-zuckerberg-a8299281.html

In our research for the search trends report, we asked 2 questions to a cluster of leading agencies about what criteria they are being selected on. The advertiser may have had a clear perspective based on precise weighted scores for a long list of factors for each participant in a pitch but the participating agencies always make their own conclusion post-selection on what made them win or not. It is those criteria that we have looked on in this research.

It is important to stress that these answers will not be representative of paid search agencies overall, as our research is using a top-down approach looking at practices in agencies that were shortlisted in Search Awards across the globe. It is also the view of the paid search team, not the view of the advertiser.

These agencies believe they were chosen on the following top 3 criteria: Strong reputation, Innovation & pioneering, Proven positive ROI

Obviously, these were not the only criteria. A number of participants considered “continuously improving campaign ROI” as a criteria. This is almost worrying, considering the state of the paid search industry where CPCs are rising, competition fierce and most campaigns reaching a certain level of maturity. It seems like a dangerous promise to be selected on – that of continuously improving ROI – but nevertheless, it is a promise, leading agencies insist on.

Next on the list was a very basic criteria – the fit between the client and the services offered. It may often be taken for granted but it has great importance. If an advertiser is looking for a specialist agency to work on paid search only, then a PPC agency with strong channel integration may not provide the right fit. And when an advertiser has an extensive offline marketing operation, using a performance-oriented paid-search agency is not the right solution. Finding the right fit is important for long-term success.

We were a bit frustrated to see the “repeatable successful process” lower on the list than “continuously improving ROI” but we were happy to see that the “quality/cost equation” was not so important – to succeed in paid search, it is important to focus on results rather than costs, hence the prominent ROI criteria

We got some additional input in the “Other” section where respondents indicated criteria like: “being thought leaders”, having a “strong team” and “high quality account management”. This seem to confirm how important the “chemistry” between an advertiser and its agency has become. The importance of the people doing the work.

But what criteria should an agency ideally be chosen on?

As mentioned in the introduction we actually asked 2 questions. We wanted to understand whether we could see a gap between on one hand what criteria paid search teams think they were chosen on and what they would ideally want to be selected on. We plotted the 2 answers on the illustration below.

So, when agency leaders dream at night, they would like for clients to choose them because they are pioneers (see “Innovation and pioneering” in the illustration) and not because of their reputation (see “Strong reputation” in the illustration). They would like clients to appreciate that they are 100% dedicated to fulfilling clients demand rather than looking at the cost.

Surprisingly, they would also like for clients to choose them for continuously improving campaign ROI, not simply on proof of positive ROI in the past.

That is pretty cocky, isn’t it?

This post is based on an extract from the #searchtrendsreport found on https://www.innovell.com/major-trends-in-paid-search/ 

Understanding the user journey is considered by the teams in our survey to be essential in order for them to do their job. These leading teams were shortlisted in search awards for their work on paid search but also cover more channels. 80% do Shopping engines, Paid Social or SEO.

Programmatic display is covered by around 70% of the sample.  Whereas paid search was their focus, they look well beyond that channel.

When asked how important it is for their team to understand the end-user journey on a scale from 0=not important to 100=essential, the sample responded with an average of 92. Understanding the end-user journey is essential to paid-search teams.

Beyond the perception aspect, our sample also use user journey mapping actively. 81% of the case studies entered by respondents in the search awards did this; furthermore, respondents carry out this user-journey mapping on an ongoing basis in 66% of the cases.

This journey is depicted by four stages through which, idealistically, an end-user passes in his or her engagement with an advertiser: awareness, consideration, conversion and loyalty.

The logic of this funnel is that you qualify and thus reduce your marketing scope when you pass from one stage to the next. This fits well with the measure-everything philosophy of digital marketing, where goal, transformation and tracking points can be established for each passage.

Whereas the movement from the consideration stage to the conversion stage is well covered by web analytics, understanding the user journey at the top of the funnel and in the loyalty stage is more difficult.

Whereas 100% of the sample included “conversion” as one of the stages they execute on, just below 20% of the respondents exclusively execute on conversion. Clearly, paid search is an active channel channel for conversion but not the only one.

The largest pattern is that of one-third of respondents, who execute on the entire user journey from awareness through to loyalty, while the second-largest group, consisting of more than one quarter of respondents, executes from awareness through to conversion.

64% execute on awareness, consideration and conversion, and two thirds of these add the loyalty stage to this. It becomes increasingly important to build as deep an understanding as possible about business levers and end-user behaviour in order to succeed in the work at the top of the funnel.

This enlarging scope for paid-search teams mirrors the overall shift that we have noticed in the sector from simple one-channel focus to a broad view over various channels and with campaigns organised in several phases.  Paid search is no longer just about conversion and paid-search teams today look well beyond the conversion stage of the user journey when defining campaign strategies

This post is based on an extract from the #searchtrendsreport found on https://www.innovell.com/major-trends-in-paid-search/ 

In our survey for the “Major Trends in Paid Search” report, we  asked a cluster of leading teams what the mix of their service offering was and were not really surprised to see « shopping » to come out top together with SEO and Paid Social.

But there was an additional parallel trend which has only become visible quite recently. The new kid on the Ad block, Amazon Ads.

In a recent analysis by eMarketer of the US ad market, Amazon Ads was projected to represent 4.61 billion in 2018 after having more than doubled since 2017. This is more than 10% of the projected Google Ads spend. This proportion of Amazon Ads to Google Ads is projected to go to 20% in 2020 for the US market. Read more in this article from eMarketer: https://www.emarketer.com/content/amazon-is-now-the-no-3-digital-ad-platform-in-the-us

[UPDATE 2019] The predictions were underestimated and the projection was increased from 4.61 billion to over 7 billion. The exact figure is not know from official accounts from Amazon but emarketers 2019 update put Amazon Ads at 18% of Google Ads already in 2018 and predict it to rise to 24% by end 2019!
https://www.emarketer.com/content/us-digital-ad-spending-will-surpass-traditional-in-2019

This is similar to the progression we originally saw with paid search eating into other advertising budgets and even to digital advertising eating into overall ad budgets. We are convinced that this is primarily down to metrics. There is nothing like proven ROI to absorb budget and the closer you are positioned to the final sale, the more convincing your ad metrics will be.

But we believe there is an additional explanation, namely the user experience. With shopping search you get colourful pictures and an increasingly smooth buying experience and in that activity Amazon has become a leader.

Leading teams have started to adopt Amazon Ads

Whereas over 80% of the teams we surveyed manage shopping engine services, it looks like it is mainly via Google Shopping or independent comparison shopping engines. Only 32% of our teams were working with Amazon Ads but we expect this to pick up quickly, especially if Amazon start opening up to paid search agencies more actively.

The teams who do, however, engage with Amazon Ads are making up for the low engagement level; in 2017 they dedicated an average of almost 12% of media spend to Amazon Ads being ahead of the market average, bringing the overall average to almost 4% on the entire sample.

Search and shopping strategies

This has given birth to a new breed of strategy, one in which the focus is entirely on optimizing the bottom of the funnel across search, Google Shopping and Amazon Ads. This is of course particularly well suited to retailers and merchants with a large product portfolio.

The more advanced search and shopping strategies will segment the products in order to identify profitability per product range and include stock level considerations. Some approaches will work on varying the product price instead of the advertising bid, as cheaper products get an algorithmic boost. Other strategies will aim to isolate top performers in individual groups and target them to the highest-performing keyword.

In Amazon Ads, where the algorithm is different, the most advanced strategies have taken advantage of the placement of ads in the right categories.

The area of search and shopping strategies is very dynamic and we expect to see more innovation moving forward: integrated approaches for Google Shopping and Amazon Ads, innovative approaches to balancing search campaign budgets on the basis of the shopping campaign performance, use of machine learning to optimize the product feeds through the CSS.

This post is based on an extract from the #searchtrendsreport found on https://www.innovell.com/major-trends-in-paid-search/

The shear amount of functionalities available to the digital marketer has exploded in recent years: new ad formats, more devices, audience targeting and automation & AI. Where the paid search equation used to be fairly simple with ads, keywords and landing pages as the three essential components of the equation, these new additions have significantly complexified the management of paid search. The changes have been faster in more recent years and Paid Search teams clearly need to organize themselves for this constant change, or as David Szetela of FMB puts it:

“Google adds and changes features in its interface on a daily basis. It takes experience and good intuition to figure out how to adapt to these changes…”

David Szetela

In our research for the Major Trends in Paid Search report, we presented the top teams that were part of our sample with a number of ways to address this challenge.

Working closely with the search engines

The top activities that more or less everybody engages in are undertaken in collaboration with the search engines: having frequent meetings with them and regularly participating in beta functionalities. Beta functionalities are new functionalities that are not open to the general public and that the search engines are in the process of testing and monitoring closely before launching them to all advertisers. The fact that almost all the top-paid search teams are engaged in these demonstrates their strong determination to progress and their fast adoption of changes and improvements. A smaller proportion (32%) take this even further and carry out joint research with the search engines.

Expert insights from blogs, newsletters, social media and more

More traditionally, around 85% of respondents read blogs containing expert insights such as Search Engine Land, Search Engine Journal, PPC Hero or State of Digital. They also subscribe to newsletters and reports (68%). Lower proportions of respondents follow influencers on social media (55%) and participate in discussion forums (41%).

Organizing think tanks

Just over 80% run internal think-tank meetings, and 32% run think-tank meetings with external participants. These are meetings designed to figure out where to take campaign strategies and how to move the business forward. These meetings can be informal, but in many cases they will use some kind of circulating responsibility where the themes will be defined up front and one person will be made responsible for presenting his or her experiences from a campaign, a test or maybe a beta functionality that has been running. In the case of external participation, this can initially take the form of a small conference. Some agencies have taken this idea further and organize their own public conferences.

On an average the sample indicated engaging with 7 different activities in order to to stay up to level and are permanently engaging in knowledge acquisition. We found that some of the most advanced teams go to the lenght of organizing their own conference or setting up a their own R&D laboratory to serve their organisation, approaches not often used in services and consulting.

This post is based on an extract from the #searchtrendsreport found on https://www.innovell.com/major-trends-in-paid-search/