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Tag: marketing

Here’s Facebook cheating you (and how to avoid it)

Here’s how Facebook is cheating advertisers with reporting of video views:

How is that cheating? Well, the advertiser implicitly assumes that ‘video views’ means people who have actually watched the video which is not the case here. Say, you have a 10-second video; this metric does not show people who have watched that video till the end, but only those who have watched the first three seconds — possibly just scrolling their newsfeeds and letting the video autoplay accidentally while quickly browsing forward. Essentially, that kind of exposure is worth closer to zero than the 1 cent Facebook usually reports.

Indeed, other view-based metrics such as CPV should be calculated based on somebody watching the video till the end, but in FB it’s 3 SECONDS after which they calculate it as a view. In effect, this will multiply the real CPV by order of several magnitudes, in some cases I’ve seen it’s 10x more than the figure reported by Facebook.

But aren’t they telling this honestly? Sure, they show the correct definition, but a large part of advertisers do not bother looking at it, or are unsuspecting misguiding definitions. After all, you should be able to trust that a big and reputable player like Facebook would not screw over advertisers. However, those of us who have played the game for many years know it’s not the first time (remember their definition of “click” a couple of years ago?).

What’s more, there’s no metric for the real CPV in the reports, so advertisers need to calculate it manually (at which point, based on my experience, it’s revealed that Facebook video views are are typically 5x more expensive than on Youtube).

How to avoid this shenanigans? Simply look at the metric ‘video views to 100%’. This is the real video views metric you should use – calculate your spend with that number, and you will get your true CPV. In other words:

ad cost / views to 100%

Keep your eyes open, my fellow advertisers!

UPDATE: Another good tactic, pointed out by my colleague Tommi Salenius, is to bid for 10-second views in your video campaigns. This is a relatively novel feature in Facebook, and although it doesn’t fix the problem, it’s a decent workaround. He also recommended to optimize “average % viewed” metric – you can do that e.g. by comparing different demographic segments. Finally, Facebook video ads can be seen to have a “social advantage” which refers to people’s ability to comment and like videos – sometimes this does take place 🙂 The advertiser can also include more text than in Youtube video ads which has a positive effect on ad prominence. It is then up to the advertiser to consider whether these advantages are worth the cost premium Facebook tends to have in comparison to Youtube.

Why human services are needed for world peace

The bot can be boss, as long as we have jobs.

Why are human services the future of our economy? (And, therefore, an absolute requirement for world peace [1].)

For three reasons:

  1. They do not pollute or waste material resources (or tend to do so with significantly less degree than material consumption)
  2. Exponential growth of population absolutely requires more human labor (supply and demand of labor)
  3. There’s no limit to service creation, but by type and nature they are infinite (because people’s needs are infinite and ever-changing)

Consequently, critical, absolutely critical measures are needed in the Western economies to enable true service economy.

Here are some ideas:

  • Taxation of human labor (VAT of services) must be drastically cut.
  • Side-costs of employing people (instead of machines) must be drastically cut.
  • Any technological solutions (e.g., platforms) increasing the match between supply and demand of human labor must be endorsed, and respectively all barriers such as cartels, removed.

Human services are the key to sustainable and socially balanced consumption – I look at Finland back in the 1950s; we were a real service economy. Today, every job possible has been replaced either by automation or by self-service (which companies call “customer participation”). We’re a digital self-service economy, not a service economy anymore.

I long for the days when we had bellboys, cleaning ladies, office clerks, research assistants and other support staff — they are important jobs which nowadays are no more. Self-service and efficiency are in fact the enemies of employment. We must consider if we want a society optimized for efficiency or one optimized for well-being (I’m starting to sound like, Bernie Sanders; which might not be a bad thing as such, but the argument has a deeper rationale in it).

Maximum efficiency is not maximum employment, far from it.

Regarding Silicon Valley and startups, there should be a counter-movement against efficiency. So far, software has been eating the world, and the world — at least in terms of job market — is becoming increasingly less. Granted, many new job types have been created to compensate for the loss, but much more is needed to fill the gap software is leaving. I think there needs to be a call for new type of startups, ones that empower human work. If you think about it, there already exists some good examples – Uber, Taskrabbit, Fiverr, Upwork are some of them. But all too often the core value proposition of a startup is based on its ability to reduce “waste” – that is, human labor.

I do not think there is any limit to creation of human services. People are never completely satisfied, and their new needs spawn new services, which in turn require new services, and so on and on. In fact, the only limit to consumption of services is one’s time and cognitive abilities! This is good and well, even hopeful if we think of the big picture. But I do think an environment needs to be created where incentives for providing human services match those of machine services, or at least approach that much more than what it currently does.

This is an issue that definitely needs to be addressed with real structural reforms in the society; as of yet, I haven’t seen ANY of that — not even discussion — in Finland. It’s as if the world was moving but the politicians were asleep, stuck in some old glory days. But in the end we all want the same thing – we want those old days BACK, when everyone had a job. It’s just that we cannot do it without adjusting the policies — radically — to the radical change of productivity which has taken place in the past decades.

It’s like another candidate — not Sanders — says: We gotta start winning again.

End notes

[1] The premise here is that the well-being of a middle class is required for a balanced and peaceful society. In contrast, the crumbling middle class will cause social unrest and wide dissatisfaction which will channel out in political radicalism, scapegoat seeking, and even wars between nations. Jobs are not just jobs, they are vehicle for peace.

The author has taught services marketing at the Turku School of Economics.

A major change in AdWords – How to react?

Introduction

Google has made a major change in AdWords. Ads are now shown only in the main column, no longer in the right column. Previously, there were generally speaking eight ads per SERP. For some queries, Google didn’t show ads at all, and additionally they’ve been constantly testing the limit, e.g. running up to 16 product listing ads per results page.

But what does that mean to an advertiser?

Analysis

The change means the number of ads shown per SERP (search-engine results page) is effectively reduced. Since the number of advertisers is not reduced (unless rotation is applied, see below), the competition intensifies. And since the visibility of search ads is based on cost-per-click auction, ceteris paribus the click prices will go up.

Therefore, logical conclusion is that when ad placements are cut, either CPC increases (due to higher competition) or impression share decreases (due to rotation). In the former, you pay more for the same number of visitors, in the latter you pay the same click price but get less visitors.

Why Google might in fact prefer ad rotation, i.e. curbing down an individual advertiser’s impression share (the number of times your ads is shown out of all possible times it could have been shown) is because that wouldn’t impact their return-on-ad-spend (ROAS) which is a relative metric. However, it would affect the absolute volume of clicks and, consequently, sales.

In some of my campaigns, I’m using a longtail positioning strategy where this will influence, since these campaigns are targeting positions 4+ which, as said, are mostly no longer available. Most likely, the change will completely eradicate the possibility of running those campaigns with my low CPC-goal.

Why did Google do this?

For Google, this is a beneficial and logical change since right column ads are commanding lower CTRs (click-through rates). This has two implications – first, they bring less money for Google since its revenue is directly associated with the number of clicks; second, as commonly known Google is using CTR as a proxy for user experience (for example, it’s a major component in Quality Score calculations which determine the true click price).

Therefore, removing the possibility of poorly performing ads while pushing the advertisers to an increased competition is a beneficial situation for Google. In the wider picture, even with higher click prices, the ROI of Google ads is not easily challenged by any other medium or channel, at least what I can see taking place in the near future.

However, for advertisers it may easily signify higher click prices and therefore decreasing returns of search advertising. This conflict of interest is unfortunate one for advertisers, especially given the skewed distribution of power in their relationship to Google.

(On a side-note, the relationship between advertisers and Google is extremely interesting. I studied that to some extent in my Master’s thesis back in 2009. You can find it here: https://www.dropbox.com/s/syaetj8m1k66oxr/10223.pdf?dl=0)

Conclusion

I recommend you revise the impact of this change on your accounts, either internally or if you’re using an agency, with them.

Dr. Joni Salminen holds a PhD in marketing from the Turku School of Economics. His research interests relate to startups, platforms, and digital marketing.

Contact email: [email protected]

Carryover effects and their measurement in Google Analytics

Introduction

Carryover effects in marketing are a tricky beast. On one hand, you don’t want to prematurely judge a campaign because the effect of advertising may be delayed. On the other hand, you don’t want bad campaigns to be defended with this same argument.

Solutions

What’s the solution then? They need to be quantified, or didn’t exist. Some ways to quantify are available in Google Analytics:

  • first, you have the time lag report of conversions – this shows how long it has taken for customers to convert
  • second, you have the possibility to increase the inspection window – by looking at a longer period, you can capture more carryover effects (e.g., you ran a major display campaign on July; looking back on December you might still see effects) [Notice that cookie duration limits the tracking, and also remember to use UTM parameters for tracking.]
  • third, you can look at assisted conversions to see the carryover effect in conversion paths – many campaigns may not directly convert, but are a part of the conversion path.

All these methods, however, are retrospective in nature. Predicting carryover effects is notoriously hard, and I’m not sure it would even be possible with such accuracy that it should be pursued.

Conclusion

In conclusion, I’d advise against being too hasty in drawing conclusion about campaign performance. This way you avoid the problem of premature judgment. The problem of shielding inferior campaigns can be tackled by using other proxy metrics of performance, such as the bounce rate. This would effectively tell you whether a campaign has even a theoretical chance of providing positive carryover effects. Indeed, regarding the prediction problem, proving the association between high bounce rate and low carryover effects would enforce this “rule of thumb” even further.

Dr. Joni Salminen holds a PhD in marketing from the Turku School of Economics. His research interests relate to startups, platforms, and digital marketing.

Contact email: [email protected]

Big data is not enough data

There is a big data fallacy

My argument here is simple – even though it’s a common argument that “everything is tracked”, marketers face a big data fallacy when assessing their ability to predict consumer behavior.

The reason is explicated here [1]:

“On any given occasion, everything from personal factors such as how well a person has slept the night before, current mood, hunger, and previous choices, to environmental variables such as the weather, the presence of other people, background music, and even ceiling height can influence how a customer responds. Algorithms can use only a handful of variables, which means a lot of weight is inevitably placed on those variables, and often the contextual information that really matters, such as the person’s current physical and emotional condition or the physical environment in which the individual is tweeting, Facebooking, or buying online, isn’t considered.”

Therefore, what is known is simply not enough to accurately predict an individual consumer’s behavior. On average, however, given the limitation of computable variables, marketing algorithms can enhance marketing performance. But data will never make marketing “perfect” – just simply because there’s not enough of it.

Endnotes

[1]: Dholakia (2015) https://hbr.org/2015/06/the-perils-of-algorithm-based-marketing

I’m into digital marketing, startups, platforms. Download my dissertation on startup dilemmas: http://goo.gl/QRc11f

How to measure offline marketing with online metrics?

Introduction

The issue with offline marketing is tracking. For many offline marketing efforts, such as exhibitions and networking events, it’s hard to track results.

Participation in these events is often expensive, and the results are evaluated on a qualitative basis. Although qualitative evaluation is better than nothing, quantitative data is obviously better. And in many cases, we can do that – all we need it the measuring mindset and a little bit of creativity.

The bottom line is: If you’re spending a lot of money into offline marketing, you have to justify its performance. Otherwise you don’t know how well the money turns into desired outcomes, let alone how well event A compared with event B in terms of performance.

The simple solution

The issue can be solved by using metrics. For example, if we are selling in a trade fair, I can use performance metrics like these:

  • sales (€, qty)
  • number of catalogs and/or flyers distributed
  • number of emails gathered via a lead-generation contest (“give us your email – win prize x”)

Of course, knowing the cost of participation, we can now calculate composite metrics such as:

  • Direct ROI = (sales – cost) / cost
  • Cost per lead (email) = cost / number of emails
  • Cost per catalogue distributed = cost / number of catalogues distributed

These can be now measured against digital channels, and evaluated whether or not we’d like to participate in the event in question again, say, next year.

Comparing offline and online performance

During my time as a marketing manager, I’ve come up with different ways to standardize the offline metrics, that is to say calculate offline marketing activities so that they are comparable with digital channels.

Here are three ways we’ve been using.

1. Cost per card

  • CPCa = cost of participation / number of business cards collected
  • Compare with: CPL

Networking is an important part of the sales cycle, especially in B2B markets. By quantifying the results, you are able to compare one event against another, as well as compare the results with lead generation (CPL) through digital channels
(for this, only include the business cards of potential customers).

2. Cost per catalog

  • CPCat = cost of distribution / number of catalogues distributed
  • Compare with: CPC

In Finland, I’ve found that catalog distribution inside magazines is a cost-effective form of marketing. This metric I compare with Google CPC, i.e. the cost of average paid user via Google. The rationale is that since the catalog is inside the customer’s favorite magazine, she will surely take a look at it (during the reading
session you tend to have more time).

3. Cost per festival contact

  • CPF = cost of participation / number of visitors
  • Compare with: CPM

Summer festivals are hot in Finland. Every year, there is more than a dozen big festivals across the country. We’re participating in some of them together with our suppliers. Festivals most often provide you with the number previous year’s visitors. I find it best to compare this metric with CPM, since the visitors are just
hypothetical contacts.

Of course, we can use several metrics, so for festivals I use CPF to evaluate which ones are the most cost-effective ones (that’s one, but the not the only criterion, since the match between us and the target audience is more important). Then, to evaluate how well we did, I’ll use the other metrics, mainly cost per lead (email) and cost per catalog distributed.

Hopefully this article gave you some useful ideas. If you have something to share, please write in in the comments. Thanks for reading.

I’m into digital marketing, startups, platforms. Download my dissertation on startup dilemmas: http://goo.gl/QRc11f

Assessing the scalability of AdWords campaigns

Introduction

Startups, and why not bigger companies, too, often test marketing channels by allocating a small budget to each channel, and then analyzing the results (e.g. CPA, cost per action) per channel.

This is done to determine a) business potential and b) channel potential. The former refers to how lucrative it is to acquire customers given their lifetime value, and the latter to how well each channel performs.

Problem

However, there is one major issue: scaling. It means that when we pour x dollars into the marketing channel in the test phase and get CPA of y dollars, will the CPA remain the same when we increase the budget to x+z dollars (say hundred times more)?

This issue can be tackled by acquiring enough data for statistical significance. This gives us confidence that the results will be similar once the budget is increased.

In AdWords, however, the scaling problem takes another form: the natural limitation of search volumes. By this I mean that at any given time, only a select number of customers are looking for a specific topic. Contrary to Facebook which has de facto an unlimited ad inventory (billions of ad impressions), Google only has a limited (although very large) ad inventory.

Solution

Here’s how to assess the scalability of AdWords campaigns:

1. Go to campaign view
2. Enable column called “Search impression share” (Modify columns –> Competitive metrics)

This will tell you how many searchers saw your ad out of all who could have seen it (this is influenced by your daily budget and bid).

In general, you want impression share to be as high as possible, given that the campaign ROI is positive. So, in general >80% is good, <10% is bad. (The exception is when running a long-tail strategy aiming for low-cost clicks, in which case <10% is okay.)

3. Calculate the scalability as follows:

scalability = clicks / impression share

For example, if you have an impression share of 40 % with which you’ve accumulated 500 clicks, by increasing your budget and bids so that you are able to capture 100% impression share, you will accumulate 1250 clicks (=500/0,40) which is the full potential of this campaign.

Limitations

Note that the formula assumes the CTR remains constant. Additionally, increasing bids may increase your CPA, so improving quality score through better ads and relevance is important to offset this effect.

Startup syndromes: “The Iznogoud Syndrome”

1. Definition

The Iznogoud Syndrome can be defined as follows:

A startup strives to disrupt existing market structures instead of adapting to them.

In most industries, existing relationships are strong, cemented and will not change due to one startup. Therefore, a better strategy is to find ways of providing utility in the existing ecosystem.

2. Origins

The name of this startup syndrome is based on the French comic character who wants to “become Caliph instead of the Caliph“, and continuously fails in that (over-ambitious) attempt. Much similarly, many startups are over-ambitious in their attempt to succeed. In my experience, they have an idealistic worldview while lacking a realistic perspective on the business landscape. While this works for some outliers – for example Steve Jobs – better results can be achieved with a realistic worldview on average. The world is driven by probabilities and hence it’s better to target averages than outliers.

3. Examples

I see them all the time. Most startups I advise in startup courses and events aim at disintermediation: they want to remove vendors from the market and replace them. For example, a startup wanted to remove recruiting agencies by making their own recruiting platform. Since recruiting agencies already have the customer relationships, it’s an unrealistic scenario. What upset me was that the team didn’t even consider providing value to the recruiting agencies, but intuitively saw them as junk to be replaced.

Another example: there is a local dominant service providing information on dance events, which holds something like 90% of market (everyone uses it). Yet, it has major usability issues. Instead of partnering with the current market leader to fix their problems, the startup wants to create its competing platform from scratch and then “steal” all users. That’s an unrealistic scenario. All around, there is too much emphasis put on disintermediation and seeing current market operators either as waste or competitors as oppose to potential partners in user acquisition, distribution or whatever.

Startups should realize they are not alone in the market, but the market has been there for a hundred years. They cannot just show up and say “hey, I’m going to change how you’ve done business for 100 years.” Or they can, but they will most likely fail. This is all well for the industry in which it doesn’t matter if 9 out of 10 fail, as the one winning brings the profits, but for an individual startup it makes more sense to get the odds of success (even average one) greater. So you see, what is good for the startup industry in general is not the same as what is good for your startup in particular.

4. Similarity to other startup syndromes

The Iznogoud syndrome is similar to “Market education syndrome”, according to which an innovation created by the startup falls short in consumer adoption regardless of its technical quality – many VC’s avoid products requiring considerable market education costs. Whereas the Market education syndrome can be seen a particular issue in B2C markets, the Iznogoud syndrome is more acute in B2B markets.

5. Recommendations

Simply put, startups should learn more about their customers or clients. They need to understand their business logic (B2B) or daily routines (B2C) and how value can be provided there. In B2B markets, there are generally two ways to provide value for clients:

  • help them sell more
  • help them cut costs

If you do so, potential clients are more likely to listen. As stated previously, this is a more realistic scenario in doing business than thinking ways of replacing them.

I’m into digital marketing, startups, platforms. Download my dissertation on startup dilemmas: http://goo.gl/QRc11f

A simple formula for assessing the feasibility of AdWords cases

Update [24th March, 2017]: In addition to the formula explained in the post, I would add the following general criteria for a good AdWords case: 1) Low-Medium competition (high CPCs force to look for alternative channels), 2) Good website/landing pages (i.e., load fast, easy to navigate, have text information relevant to the keywords.

Introduction

Google AdWords is a form of on-demand marketing which matches demand (keywords) with supply (ads). Because it provides good relevance between demand and supply, it efficiently fulfills the core purpose of marketing which is, again, to match supply and demand. However, while this property of AdWords makes it generally much more effective than other forms of online marketing, it also leads to a major limitation: the campaigns cannot scale beyond natural search volumes.

I often tell this to my students participating in the Google Online Marketing Challenge (GOMC), but a few of them always fall into the “trap of low search volume”. I will explain this in the following.

Selection criteria

First, the relevant dimensions for assessing the potential in AdWords are:

  • geographic range: the based on the company’s offerings
  • product range

These can vary from low to high so that

Low geographic range x Low product range = Trap of low search volume

Low geographic range x High product range = Potential risk of low search volume

High geographic range x Low product range = Potential risk of low search volume

High geographic range x High product range = High search volume (Best case for AdWords)

In other words, this formula favors companies with nationwide distribution and large product range. These campaigns tend to scale the best and offer the best ratio between cost and value of optimization. In contrast, local business with one or two products or services are the least feasible candidates.

What does the trap of limited search volume mean?

Well, first of all it means the spend will be low. In GOMC, this means some teams struggle to spend the required $250 during the three-week campaign window.

Second, and more importantly, it means these cases are less interesting for marketers. They offer little room for optimization (because spend is low and there is very little data to work with).

Also for this reason the management cost of running these campaigns (=the amount a marketer can charge for his/her services) can become unbalanced: for example, if the yearly spend of a low-volume campaign is, say $400 and the marketers charges $100 per hour for his/her work, there is no point for client to pay for many working hours, as their cost quickly exceeds that of the media budget.

Conclusion

As a marketer, you always want to select the best case to amplify with your skills. You can think of it through two dimensions:

  • marketing
  • product

By multiplying them, we get the following.

Bad marketing x Bad product = Bad results

Bad marketing x Good product = Okay results

Good marketing x Bad product = Bad results

Good marketing x Good product = Good results

The same in numbers:

0 x 0 = 0

0 x 1 = 0

1 x 0 = 0

1 x 1 = 1

In other words, it makes sense to choose a case which is good for you as a marketer. A good case will work decently with bad marketing, but not vice versa. And only coupled with good marketing will the maximum potential of a good product be achieved.

Author:

Joni Salminen
Ph.D., marketing

Crowdfunding pitch to media – an example

Here’s an example on how to do PR for a crowdfunding campaign. It should be sent at least a couple of weeks prior to launch.

Hi [name],

this is [yourname] from [yourcompany].

We are preparing to release a new product in [yourplatform], and I wanted to give you heads-up since you wrote about [a competitor] six months ago. Our product is similar, but better 😉

Here’s why it is better:

  • [reason 1]
  • [reason 2]
  • [reason 3]

Here’s a link to press material including pictures and more information: [link]

The campaign will be launched on [date], so I hope you’d publish an article about us at around that time.

In the meantime, I’m of course available for any questions / comments!

Have a nice day,

[yourname] from [www.yourwebsite.com]

Tel. [telephone]

Skype: [Skype]

Email: [email]