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Tag: Google Adwords

Managing business development of an ad platform

Here’s a great example of a business development program of an ad platform:

Google provides similar service through its AdWords Partner program. Facebook and Google are offering the free 1-on-1 help for one simple reason:

It improves the quality of ads.

Because of this, two positive effects take place:

a) the users are happier. As two-sided markets, FB and Google need to constantly monitor and improve the experience for both sides, users and advertisers. Particularly, they need to curb the potential negative indirect network effect resulting from bad ads.

b) the results are better. Most of FB’s +2M advertisers are small businesses and lack expertise – with expert guidance, they will use the funtionalities of the ad platform better and will see better results. This prompts an increased investment in the ads, which increases the platform’s revenues.

Thus, this program is an example of a win-win-win business development program of a platform. The users are shown better ads, the advertiser gets better results and the platform increases its revenue. Given that FB and Google conduct some “lead scoring” to choose the advertisers with the most growth potential, the ROI of these efforts is almost certainly positive.


With these programs, FB and Google are once again beating the traditional media industry that has very weak support in managing online advertising. Basically, no interest in the client after getting the money. To do better in competition, traditional publishers need to help their clients optimize and increase the quality of their ads, as well as improve their core technology to close the gap between them and FB and Google.

How to Win the Google Online Marketing Challenge

GOMCHA European Winners 2016

1. Introduction

In the past couple of weeks, a few people have approached me asking for tips on how to do well in the Google Online Marketing Challenge. So, I thought I might as well gather some of my experiences in a blog post, and share them with everybody.

A little bit of background: I’ve been the professor of two winning teams (GOMC Europe 2013 & GOMC Europe 2016). Although the most credit is obviously due to the students that do all the hard work (the students at Turku School of Economics simply rock!), guidance does play an important role since most commonly the students have no prior experience in SEM/PPC, and need to be taught quickly where to focus on.

2. Advice to teachers

The target audience for this post is anyone participating in the challenge. For the teachers, I have one important advice:

Learn the system if you’re teaching it. There’s no substitute for real experience. The students are likely to have a million questions, and you need to give better answers than “google it.” Personally, I was fortunate enough to have done SEM for many years before starting to teach it. Without that experience, it would have been impossible to guide the teams do well. However, if you don’t have the same advantage, but you want your students to do well, turn to the industry. Many SEM companies out there are interested in mentoring/sparring the students, because that way they can also spot talented individuals for future hiring (win-win, right?).

3. How to win GOMCHA?

3.1 Overview

That said, here are my TOP3 “critical success factors” for winning the challenge:

  1. Choose your case wisely
  2. Focus on Quality Score
  3. Show impact

That’s it! Follow these principles and you will do well. Now, that being said, behind each of them is a whole layer of complexity ūüôā Let‚Äôs explore each point.

3.2 Choosing the AdWords case

First, one of the earliest questions students are going to ask is how to choose the company/organization they’re doing the campaign for. And that‚Äôs also one of the most important ones. How I do it: I let each team choose and find their own case; however, I tell them what is a good case and what is not. I wrote a separate post about choosing a good AdWords case. Read the post, and internalize the information.

Update: one more point to the linked post – choose one that preferably has some brand searches already. This helps you get higher overall CTR, and lower the overall CPC.

The choice of a good case is crucial, because you can be the best optimizer in the world, but if you have a bad case, you will fail. An example was a team that chose a coffee company — it was not a good case to choose because it had low product range and relatively few searches. For some reason, the team, which consisted of several students with *real experience* in AdWords, wanted to choose it. Not surprisingly, they struggled due to the above reasons and were easily overshadowed by other teams with no experience but a good case. Therefore, the formula here is: success = case * skills.

By the way, that is one of the most important lessons for any marketing student in general: Always choose your case wisely, and never market something whose potential you don’t believe in.

3.3 Choosing the metrics

Another common question relates to the metrics: What should we optimize for? While there are many important metrics, including CTR and CPC, I would say one is above the others. That is clearly the Quality Score, which seems to be very influential in Google’s ranking algorithm for the competition.

Note that I don‚Äôt have any insider information on this, but I‚Äôm saying *seems* because of this reason: In 2015, I instructed the teams to focus on a wide range of metrics, including CTR, CPC, and QS. What came out where several great teams that, in my opinion, had better overall metrics than many of the finalists that year (none of my teams were finalists). Last year, however, I switched the strategy and instructed the teams to heavily focus on Quality Score, even at the cost of other metrics. For example, to the team that ended up winning in 2016, I said “your goal is 10 x 10”, meaning they should get 10 keywords with QS 10. They ended up getting 12, and the rest is history ūüôā

3.4 Why is Quality Score that important?

In my view, it’s because all optimization efforts basically culminate to that metric. To maximize your QS, you essentially need to do all the right things in terms of optimization, including account structure, ad creation, and landing pages. To get these things nailed, refer to this post. And google for more tips: blogs such as PPC Hero, Wordstream, and Certified Knowledge have plenty of subject matter to learn from. I also have complied an extensive list of digital marketing blogs that you can utilize.

However, do note that all third-party information is to some degree unreliable. Use it with caution, combined with your first-hand experiments (i.e., do what you see working the best in the light of numbers). The most reliable source of information is of course Google, because they know the system from the inside, any of the experts (including myself) don’t. So, use Google’s AdWords help as your main reference.

3.5 Show real impact

The last step, since many teams can score high on metrics, is to show real-life impact. This is pretty much the only way to differentiate when all finalist teams are good. The thing you can do here is, first of all, to meticulously follow Google’s guidelines for the reports to highlight your greatness. As a member of the academic panel, I know some cases have been failed due to not following the technical guidelines, so make sure your output is in line with them. However, that is not the main point; the main point is to show how you brought real results to your case organization. Although not part of the official ranking, if you look at the past winners, most of them have gained a lot of conversions. By knowing that, you can do the math. The reports of the winners from earlier years can be found at the challenge website.

4. List of practical tips

Finally, some practical tips (the list is in no particular order, and not comprehensive at all):

  1. Optimize every day like you were obsessed with AdWords
  2. Don’t be afraid to ask advice from the experts; take every help you can get to learn faster
  3. Prefer using ‚Äėexact match‚Äô keywords
  4. Never mix display campaigns with search campaigns (i.e., avoid ‚Äėdisplay select‚Äô)
  5. Avoid GDN altogether; you can experiment with it using a little budget, but focus 99% on search campaigns
  6. When possible, direct the keywords to a specific landing page (not homepage)
  7. Create ad groups based on semantic similarity of keywords (if you don’t know what this means, find out)
  8. Don’t stress about the initial bid price; set it at some level based on the Keyword Planner estimates and change according to results
  9. Or, alternatively, set it as high as possible to get a good Avg. Pos. and therefore improved CTR, and improved QS
  10. Set the bid price manually per keyword
  11. Use GA to report after-click performance (good for campaign report)
  12. Use as many AdWords features as possible (good for campaign report)

Finally, read Google’s materials, including the challenge website. Follow their advice meticulously, and read read read about search-engine advertising from digital marketing blogs and Google’s website.

Good luck!! ūüôā

CAVEAT: I‚Äôm a member at the Google Online Marketing Challenge‚Äôs academic panel. These are my personal opinions and don’t necessarily represent the official panel views. The current judging criteria for the competition can be found at:

UPDATE (May, 2017): Together with Elina Ojala (next to me in the picture above), we had a Skype call with students of Lappeenranta University of Technology (LUT). Elina pointed out some critical things: it’s important 1) to be motivated, 2) have a really good team without free riding, 3) share tasks efficiently (e.g., analytics, copywriting; based on individual interests), and 3) go through extra effort (e.g., changing the landing pages, using GA). I added that for teachers it’s important to motivate the students: aim HIGH !! And to stress there is¬†zero chance of winning if the team doesn’t work every day (=linear relationship between hours worked and performance).

Resources (some in Finnish)

Rule-based AdWords bidding: Hazardous loops

1. Introduction

In rule-based bidding, you want to sometimes have step-backs where you first adjust your bid based on a given condition, and then adjust it back after the condition has passed.

An example. An use case would be to decrease bids for weekend, and increase back to normal level for weekdays.

However, defining the step-back rate is not done how most people would think. I’ll tell you how.

2. Step-back bidding

For step-back bidding you need two rules: one to change the bid (increase/decrease) and another one to do the opposite (decrease/increase). The values applied by these rules must cancel one another.

So, if your first rule raises the bid from $1 to $2, you want the second rule to drop it back to $1.

Call these

x = raise by percentage

y = lower by percentage

Where most people get confused is by assuming x=y, so that you use the same value for both the rules.

Example 1:

x = raise by 15%

y = lower by 15%

That should get us back to our original bid, right? Wrong.

If you do the math (1*1.15*0.85), you get 0.997, whereas you want 1 (to get back to the baseline).

The more you iterate with the wrong step-back value, the farther from the baseline you end. To illustrate, see the following simulation, where the loop is applied weekly for three months (12 weeks * 2 = 24 data points).

Figure 1 Bidding loop

As you can see, the wrong method will take you more and more off from the correct pattern as the time goes by. For a weekly rule the difference might be manageable, especially if the rule’s incremental change is small, but imagine if you are running the rule daily or each time you bid (intra-day).

3. Solution

So, how to get to 1?

It’s very simple, really. Consider

  • B = baseline value (your original bid)
  • x = the value of the first rule (e.g., raise bid by 15% –> 0.15)
  • y = the value of the second rule (dependant on the 1st rule)

You want to solve y from

B(1+x) * y = 1

That is,

y = 1 / B(1+x)

For the value in Example 1,

y = 1 / 1*(1+0.15)

multiplying that by the increased value results in 1, so that

1.15 * (1/1*(1+0.15) = 1


Remember to consider elementary mathematics, when applying AdWords bidding rules!

Total remarketing – the concept

Here’s a definition:

Total remarketing is remarketing in all possible channels with all possible list combinations.


  • Programmatic display networks (e.g., Adroll)
  • Google (GDN, RLSA)
  • Facebook (Website Custom Audience)
  • Facebook (Video viewers / Engaged with ads)
  • etc.

How to apply:

  1. Test 2-3 different value propositions per group
  2. Prefer up-selling and cross-selling over discounts (the goal is to increase AOV, not reduce it; e.g. you can include an $20 gift voucher when basket size exceeds $100)
  3. Configure well; exclude those who bought; use information you have to improve remarketing focus (e.g. time of site, products or categories visited — the same remarketing for all groups is like the same marketing for all groups)
  4. Consider automation options (dynamic retargeting; behavior based campaign suggestions for the target)

In 2016, Facebook bypassed Google in ads. Here’s why.


The gone 2016 was the first year I thought Facebook ends up beating Google in the ad race, despite the fact Google still dominates in revenue ($67Bn vs. $17Bn in 2015). I’ll explain why.

First, consider that Google’s growth is restricted by three things:

  1. natural demand
  2. keyword volumes, and
  3. approach of perfect market.

More demand than supply

First, at any given time there is a limited number of people interested in a product/service. The interest can be of purchase intent or just general interest, but either way it translates into searches. Each search is an impression that Google can sell to advertisers through its AdWords bidding. The major problem is this: even when I’d like to spend more money on AdWords, I cannot. There is simply not enough search volume to satisfy my budget (in many cases there is, but in highly targeted and profitable campaigns many times there isn’t). So, the excess budget I will spend elsewhere where the profitable ad inventory is not limited (that is, Facebook at the moment).

Limited growth

According to estimates, search volume is growing by 10-15% annually [1]. Yet, Google’s revenue is expected to grow even by 26% [2]. Over the year, Google’s growth rate in terms of search volume has substantially decreased, although this is perceived as a natural phenomenon (after trillion searches it’s hard to keep growing double digits). In any case, the aforementioned dynamics reflect to search volumes – when the volumes don’t grow much and new advertisers keep entering the ad auction, there is more competition over the same searches. In other words, supply stays stable but demand increases, resulting in more intense bid wars.

Approaching perfect market

For a long time now, I’ve added +15% increase in internal budgeting for AdWords, and last year that was hard to maintain. Google is still a profitable channel, but the advertisers’ surplus is decreasing year by year, incentivizing them to look for alternative channels. While Google is restrained by its natural search volumes, Facebook’s ad inventory (=impressions) are practically limitless. The closer AdWords gets to a perfect market (=no economic rents), the less attractive it is for savvy marketers. Facebook is less exploited, and allows rents.

What will Google do?

Finally, I don’t like the Alphabet business. Already in the beginning it signals to investors that Google is in “whatever comes to mind” business instead of strategic focus on search. Most likely Alphabet ends up draining resources from the mother company, producing loss and taking human capital off from succeeding in online ads business (which is where their money comes from). In contrast, Facebook is very focused on social; it buys off competitors and improves fast. That said, I do have to recognize that Google’s advertising system is still much better than that of Facebook, and in fact still the best in the world. But momentum seems to be shifting to Facebook’s side.


The maximum number of impressions (=ad inventory) of Facebook is much higher than that of Google, because Google is limited by natural demand and Facebook is not. In the marketplace, there is always more supply than demand which is why advertisers want to spend more than what Google enables. These factors combined with Facebook’s continously increasing ability to match interested people with the right type of ads, makes Facebook’s revenue potential much bigger than Google’s.

From advertiser’s perspective, Facebook and Google both are and are not competitors. They are competitors for ad revenue, but they are not competitors in the online channel mix. Because Google is for demand capture and Facebook for demand creation, most marketers want to include both in their channel mix. This means Google’s share of online ad revenue might decrease, but a rational online advertisers will not drop its use so it will remain as a (less important) channel into foreseeable future.




Advertisers actively following “Opportunities” in Google AdWords risk bid wars

PPC bidding requires strategic thinking.

Introduction. Wow. I was doing some SEM optimization in Google AdWords while a thought struck me. It is this: Advertisers actively following “Opportunities” in AdWords risk bid wars. Why is that? I’ll explain.

Opportunities or not? The “Opportunities” feature proposes bid increases for given keywords, e.g. Week 1: Advertiser A has current bid b_a and is proposed a marginal cost m_a, so the new bid e_a = b_a+m_a. During the same Week 1: Advertiser B, in response to Advertiser A’s acceptance of bid increase, is recommended to maintain his current impression share by increasing his bid b_b to e_b = b_b+m_b. To maintain the impression share balance, Advertiser A is again in the following optimization period (say the optimization cycle is a week, so next week) proposed yet another marginal increase, et cetera.

If we turn m into a multiplier, then the bid will eventually be b_a = (b_a * m_a)^c, where c is the number of optimization cycles. Let’s say AdWords recommends 15% bid increase at each cycle (e.g., 0.20 -> 0.23$ in the 1st cycle); then after five cycles, the keyword bid has doubled compared to the baseline (illustrated in the picture).

Figure 1   Compounding bid increases

Alluring simplicity. Bidding wars were always a possible scenario in PPC advertising – however, the real issues here is simplicity. The improved “Opportunities” feature gives much better recommendations to advertisers than earlier version, which increases its usage and more easily leads into “lightly made” acceptance of bid increases that Google can show to likely maintain a bidder’s current competitive positioning. From auction psychology we know that bidders have a tendency to overbid when put into competitive pressure, and that’s exactly where Google is putting them.

It’s rational, too. I think that more aggressive bidding can easily take place under the increasing usage of “Opportunities”. Basically, the baselines shift at the end of each optimization cycle. The mutual increase of bids (i.e., bid war) is not only a potential outcome of light-headed bidding, but in fact increasing bids is rational as long as keywords still remain profitable. But in either case, economic rents (=excessive profits) will be competed away.

Conclusion. Most likely Google advertising will continue converging into a perfect market, where it is harder and harder for individual advertisers to extract rents, especially in long-term competition. “Opportunities” is one way of making auctions more transparent and encourage more aggressive bidding behavior. It would be interesting to examine if careless bidding is associated with the use of “Opportunities” (i.e., psychological aspect), and also if Google shows more recommendations to increase than decrease bids (i.e., opportunistic recommendations).

Keyword optimization routine for search-engine advertising (AdWords)

In this post, I’m sharing a simple optimization process for search-engine advertising. I’ll also try to explain its rationale, i.e. explanation of why it should work. The process is particularly applicable to Google AdWords due to availability of metrics, but for the most parts it applies to Bing Ads as well.

First, take a list of your keywords along with the metrics defined in the following.

Then, sort by cost (high to low). Why? Because you may have thousands of keywords, out of which a handful matter for generating results — the Pareto principle is strong in search advertising. It makes sense to focus your time and effort on optimizing the keywords that make up most of your spend.

In metrics, look at

  • relevance (subjective evaluation)
  • match type –> if broad, switch to exact
  • impression share –> if low (below 70%), increase bid (all else equal)
  • cost per converted click –> if high¬†(above¬†CPA target), reduce bid
  • avg. position –> if low (below 3), increase bid (all else equal)
  • Quality Score –> if low (below 6), improve ad group structure, ad copy and/or landing pages

Relevance is the first and foremost. Ask yourself: is this a keyword people who are interested in my offering would use? Sometimes you may include terms you’re not unsure of, or because you want to achieve a certain volume of clicks. If you are able to achieve that volume with relative ease, you don’t need expansion but reduction of keywords. Reduction is started from the keywords with the lowest relevance – interpreted firstly by the results of a keyword (data trumps opinions) and secondarily by qualitative evaluation of the keywords according to the aforementioned rationale.

A common strategy is to¬†start with broad match, and gradually move towards exact match. Take a look at the search terms report: are you getting a lot of irrelevant searches? If so, it definitely makes sense not only to include negative keywords but also to change the match type. Generally speaking, as the number of optimization cycles increases the number of broad match keywords decreases. In the end, you only have exact terms. However, this assumes you’re able to achieve click volume goals.

Are you getting enough impressions? Impression share indicates your keywords’ competitiveness in ad¬†auctions. If relevance is high and impression share low, you especially want to take action in improving your competitiveness. The simplest step is to increase keyword bid. Depending on the baseline, performance, and SEA strategy, you may want to increase it by 30% or even 100% to get a real impact.

Regarding the goals, you should know your CPA target. A very basic way to calculate is by multiplying average order value with average profit per order, i.e. calculate your margin. The amount equivalent to margin is the maximum you can spend to remain profitable or at break-even. (Of course, the real pros consider customer lifetime value at this point, but for simplicity I’m leaving it out here.)

Average position matters because an ad with a high rank gains a natural lift. That is, you can run the same ad in position 3 and position 1 and get better results in position 1 just because it is position (not because the ad is better). This in turn influences your click-through rate and indirectly boosts your Quality Score which, in turn, reduces your CPC, all else being equal. Other ways to improve QS are to re-structure ad groups, usually by reducing the number of keywords and focusing on semantic similarity between the terms, writing better ad copy that encourages people to click (remember, no ad is perfect!), and improving landing page experience if that is identified as a weak component in your Quality Score evaluation.

This is what I pay attention to when optimizing keywords in search advertising. Feel free to share your comments!

Ohjelmallisen ostamisen alusta: ideaaliominaisuuksia

Full-metal digitalist.

Maailma muuttuu, markkinoijani

Tällä hetkellä digitaalinen media on siirtymässä ohjelmallisen ostamisen malliin, ts. mainokset ostetaan ja myydään mainosalustan (esim. Google AdWords, Facebook) kautta. Myös perinteinen offline-media (TV, printti, radio) tulee ajan myötä siirtymään ohjelmallisen ostamisen järjestelmiin, joskin tässä menee arvioni mukaan vielä 5-10 vuotta.

Miksi ohjelmallinen ostaminen voittaa?

Syy on selkeä:

Ohjelmallinen ostaminen on lähtökohtaisesti aina tehokkaampaa kuin vaihdanta ihmisten välityksellä.

Taloustieteen näkökulmasta tarkasteltuna mainosvaihdantaan, kuten kaikkeen vaihdantaan, liittyy transaktiokustannuksia: hinnan neuvottelu, paketointi, yhteydenpito, kysymykset, mainosten lähettäminen, raportointi jne. Tämä on ihmistyötä joka maksaa aikaa ja vaivaa, eikä johda optimiratkaisuun hinnan tai mainonnan tehokkuuden kannalta.

Ihminen häviää aina algoritmille tehokkuudessa, ja mainonta on tehokkuuspeliä.

Edell√§ mainitut transaktiokustannukset¬†voidaan minimoida ohjelmallisen ostamisen kautta. Mediamyyji√§ ei yksinkertaisesti tarvita en√§√§ t√§ss√§ prosessissa; samalla mainonnasta tulee halvempaa ja demokraattisempaa. Toki siirtym√§vaiheessa tulee olemaan siirtym√§kipuja, etenkin liittyen organisaatiorakenteen muutokseen ja kompetenssin p√§ivitt√§miseen. Bisneslogiikassa on my√∂s siirrytt√§v√§ “premium”-ajattelusta vapaaseen markkina-ajatteluun: mainostila on vain sen arvoinen kuin siit√§ saatavat tulokset ovat mainostajalle — n√§m√§ tulevat olemaan pienempi√§ kuin mediatalojen nykyinen hinnoittelu, mik√§ onkin negatiivinen kannustin siirtym√§n hyv√§ksymiseen.

Mitkä ovat menestyksekkään ohjelmallisen ostamisen alustan ominaisuuksia?

Näkemykseni mukaan niitä ovat ainakin nämä:

  • matala aloituskustannus: tarvitaan vain 5 euron budjetti aloittamiseen (n√§in saadaan likviditeetti√§ alustalle, koska my√∂s pienmainostajien on kannattavaa l√§hte√§ kokeilemaan)
  • budjettivapaus: mainostaja voi vapaasti m√§√§ritt√§√§ budjetin, ei minimispendi√§ (ks. edell√§)
  • markkinapohjainen hinnoittelu: tyypillisesti algoritminen huutokauppamalli, joka kannustaa totuudenmukaiseen huutamiseen (vrt. Googlen GSP¬†ja Facebookin VCG-malli)
  • suorituspohjaisuus: hinnoittelukomponentti, jolla “palkitaan” parempia mainostajia ja n√§in kompensoidaan mainonnan haittoja loppuk√§ytt√§j√§lle
  • vapaa kohdennus: mainostaja voi itse m√§√§ritt√§√§ kohdennuksen (t√§m√§n EI tule olla mediatalon “salattua tietoa”)

Nämä ominaisuudet ovat tärkeitä, koska kansainväliset kilpailijat jo tarjoavat ne, ja lisäksi ne on osoitettu toimiviksi niin teoreettisessa kuin käytännöllisessä tarkastelussa.

Tärkeitä näkökulmia mainostajan näkökulmasta ovat:

  • demokraattisuus: kuka vain voi p√§√§st√§ alustalle ja k√§ytt√§√§ sit√§ itsepalveluna
  • tulospohjaisuus: maksetaan toteutuneista klikeist√§/myynneist√§, ei ainoastaan n√§yt√∂ist√§
  • kohdennettavuus: mainostaja voi itse s√§√§t√§√§ kohdennuksen, mik√§ nostaa relevanssin mahdollisuutta ja n√§in v√§hent√§√§ mainonnan negatiivista verkostovaikutusta (ts. asiakkaiden √§rsyyntymist√§)

Kohdennusvaihtoehtoja voivat olla esim.

  • kontekstuaalinen kohdennus (sis√§ll√∂n ja mainostajan valitsemien avainsanojen yhteensopivuus)
  • demograafinen kohdennus (ik√§, sukupuoli, kieli)
  • maantieteellinen kohdennus
  • k√§vij√§n kiinnostuksen kohteet

Osa näistä voi olla mediataloille hankalia selvitettäviä, ainakaan hankalampaa kuin Facebookille Рkohdennus on kuitenkin mainonnan onnistumisen kannalta kriittinen seikka, joten tietojen saamiseksi on tehtävä työtä.


Ohjelmallisen ostamisen alustat ovat mediatalon ydinkompetenssia, eivät ostopalvelu. Siksi uskonkin, että alan toimijat lähtevät aggressiivisesti kehittämään kompetenssiaan alustojen kehittämisessä. Tai muuten ne jatkavat mainoskakun häviämistä Googlen ja Facebookin kaltaisille toimijoille, jotka tarjoavat edellä mainitut hyödyt.

Kirjoitin muuten¬†mainosvaihdannasta pro gradun otsikolla “Power of Google: A study on online advertising exchange” vuonna 2009 — jo siin√§ sivuttiin n√§it√§ aiheita.

Joni Salminen
KTT, markkinointi
[email protected]

Kirjoittaja opettaa digitaalista markkinointia Turun kauppakorkeakoulussa.

A Little Guide to AdWords Optimization

Hello, my young padawan!

This time I will write a fairly concise post about optimizing Google AdWords campaigns.

As usual, my students gave¬†the inspiration to this post. They’re currently participating in Google Online Marketing Challenge, and — from the mouths of children you hear the truth ūüôā — asked a very simple question: “What do we do when the campaigns are running?”

At first, I’m tempted to say that you’ll do optimization in my supervision, e.g. change the ad texts, pause add and change bids of keywords, etc. But then I decide to write them a brief introduction.

So, here it goes:

1. Structure – have the campaigns been named logically? (i.e., to mirror the website and its goals)? Are the ad groups tight enough? (i.e., include only semantically similar terms that can be targeted by writing very specific ads)

2. Settings – all features enabled, only search network, no search partners (– that applies to Google campaigns, in display network you have different rules but never ever mix the two under one campaign), language targeting Finnish English Swedish (languages that Finns use in Google)

3. Modifiers – are you using location or mobile bid modifiers? Should you? (If unsure, find out quick!)

4. Do you have need for display campaigns? If so, use display builder to build nice-looking ads; your targeting options are contextual targeting (keywords), managed placements (use Display Planner to find suitable sites), audience lists (remarketing), and affinity and topic categories (the former targets people with a given interest, the latter websites categorized under a given interest, e.g. traveling) (you can use many of these in one campaign)

5. Do you have enough keywords to reach the target daily spend? (Good to have more than 100, even thousands of keywords in the beginning.)

6. What match types are you using? You can start from broad, but gradually move towards exact match because it gives you the greatest control over which auctions you participate in.

7. What are your options to expand keyword base?¬†Look for opportunities by taking a search term report from all keywords after you’ve run the campaign for week or so; this way you can also identify more negative keywords.

8. What negative keywords are you using? Very important to exclude yourself from auctions which are irrelevant for your business.

9. Pausing keywords — don’t delete anything ever, because then you’ll lose the analytical trace; but frequently stop keywords that are a) the most expensive and/or b) have the lowest CTR/Quality Score

10. Have you set bids at the keyword level? You should – it’s okay to start by setting the bid at ad group level, and then move gradually to keyword level as you begin to accumulate real data from the keyword market.

11. Ad positions – see if you’re competitive by looking at auction insights report; if you have low average positions (below 3), consider either pausing the keyword or increasing your bid (and relevance to ad — very important)

12. Are you running good ads? Remember, it’s all about text. You need to write good copy which is relevant to searchers. No marketing bullshit, please. Consider your copy as an answer to searchers request; it’s a service, not a sales pitch. This topic deserves its own post (and you’ll find them by googling), but as for now, know that the best way (in my opinion) is to have 2 ads per ad group constantly competing against one another. Then pause the losing ad and write a new contender — remember also that an ad can never be perfect: if your CTR is 10%, it’s really good but with a better ad you can have 11%.

13. Landing page relevance – you can see landing page experience¬†by hovering over keywords – if the landing page experience is poor, think if you can instruct your client to make changes, or if you can change the landing page to a better one. The landing page relevance comes from the searcher’s perspective: when writing the search query, he needs to be shown ads that are relevant to that query and then directed to a webpage which is the closest match to that query. Simple in theory, in practice it’s your job to make sure there’s no mismatch here.

14. Quality Score – this is the godlike metric of AdWords. Anything below 4 is bad, so pause it or if it’s relevant for your business, then do your best to improve it. The closer you get to 10, the better (with no data, the default is 6).

15. Ad extensions – every possible ad extension should be in use, because they tend to gather a good CTR and also positively influence your Quality Score. So, this includes sitelinks, call extensions, reviews, etc.

And, finally, important metrics. You should always customize your column views at campaign, ad group and keyword level. The picture below gives an example of what I think are generally useful metrics to show — these may vary somewhat based on your case. (They can be the same for all levels, except keyword level should also include Quality Score.)

  • CTR (as high as possible, at least 5%)
  • CPC (as low as possible, in Finland 0.20‚ā¨ sounds decent in most industries)
  • impression share (as high as possible WHEN business-relevant keywords, in long-tail campaigns it can be low with a good reason of getting cheap traffic; generally speaking, this indicates¬†scaling potential; I’ve written a separate post about this, you can find it by looking at my posts)
  • Quality Score (as high as possible, scale 1-10)
  • Cost (useful to sort by cost to focus on the most expensive keywords and campaigns)
  • Avg. position (TOP3 is a good goal!)
  • Bounce rate (as low as possible, it tends to be around 40% on an average website) (this only shows if GA is connected –> connect if possible)
  • Conversion rate (as high as possible, tends to be 1-2% in ecommerce sites, more when conversion is not purchase)
  • Number of conversions (shows absolute performance difference between campaigns)

That’s it! Hope you enjoyed this post, and please leave comments if you have anything to add.

Example of Google’s Moral Hazard: Pooling in Ad Auctions

Google has an incentive to group advertisers in ad auction even when this conflicts with the goals of an individual advertiser.

For example, you’d like to bid on ‘term x‘ and would not like be included in auctions ‘term x+n‘ due to e.g. lower relevance, your ad might still participate in the auction.

This relates to two features:

  1. use of synonyms — by increasing the use of synonyms, Google is able to pool more advertisers in the same ad auction
  2. broad match — by increasing the use of broad match, Google is able to pool more advertisers in the same ad auction

Simply put, the more bidders competing in the same ad auction, the higher the click price and therefore Google’s profit. It needs to be remarked that pooling not only increases the CPC of existing ad auctions by increasing competition, but it also creates new auctions altogether (because there needs to be a minimum number of bidders for ads to be launched on the SERP).

A practical example of this moral hazard is Google’s removal of ‘do not include synonyms or close variants‘ in the AdWords campaign settings, which took place¬†a couple of years ago.

There are two ways advertisers can counter this effect:

  1. First, by efficient use of negative keywords.
  2. Second, by resorting to multi-word exact matches as much as possible.

In conclusion, I always tell my students that Google is a strategic agent that wants to optimize its own gain — as far as its and advertiser’s goals are aligned, everything is fine, but there are these special cases in which the goals deviate and the advertisers needs to recognize them and take action.