But while ad scheduling in Google AdWords can be extremely powerful in boosting campaign performance, it is essential that ad scheduling decisions are reliable and informed. Since so many internal and external factors can bias your day of the week analysis, advanced ad scheduling strategies are best reserved for mature and relatively stable PPC campaigns with a large amount of conversion data.

Below are three tips for getting the most out of ad scheduling, and suggestions to help you make reliable and informed decisions to take advantage of this powerful feature of Google AdWords.

1. Beware of Diluted Data

You’re dividing your conversion data across 7 days, so each day will considerably less data than if you look at your campaign on the whole. Keep this in mind, and avoid jumping to conclusions based on insufficient data.

Recommendations: If you’re identified Friday as being a high-performing day, only make slight adjustments to your ad scheduling. Just because Friday has worked better than Saturday does not mean Friday should have bids 100% higher than Saturday. Exaggerated changes to ad scheduling can turn an otherwise high-performing campaign into a poor-performing one.

2. Look for Trends

Avoid getting caught up in the detail. You’re right – Wednesday did perform better than Thursday, but is it really significant? A handful fewer sales on Wednesday and a handful more on Thursday would result in both days performing exactly the same.

Recommendations: Take a step back and look for more general and reliable insights. It is clear that Mondays – Fridays performed much better than Saturdays and Sundays, so make that your only finding from your analysis. Trying to distinguish between individual days where performance is so similar is unnecessarily complicating and confusing your ad scheduling strategy.

3. The Past is Not the Future

Just because Saturdays and Sundays have performed poorly in the past, and Thursdays have performed well, does not mean they will continue to do so in the future. Perhaps a PR campaign caused a sudden increase in sales one Thursday which is biasing the results? Perhaps you tested some new high-volume keywords one weekend which were paused after the weekend due to few sales?

Recommendations: Where possible, repeat your analysis using different date ranges, to see if your findings are recreated. If certain days consistently and significantly outperform other days across different periods, then feel free to incorporate that into your ad scheduling. But avoid making changes to ad scheduling if too many external factors could have influenced day of week performance.

Slow and Steady Wins the Race

Ad scheduling can be extremely useful for mature PPC campaigns which have benefited from a steady period of ad visibility, with limited changes to keywords, bids, ads, and landing pages. If a PPC campaign is in its early growth phrase, where multiple testings and optimisations make reliable day of week analysis difficult, keep day of week analysis for another time.

Does ad scheduling help you boost PPC profitability? Do weekdays consistently perform better than weekends? Share your thoughts and comments below.

1. Identify irrelevant keywords which can be added as negatives
2. Identify new keyword opportunities for keyword expansion

The difficulty, however, is efficiently and reliably pulling out trends and insights from a raw search query report. According to Google, 25% of searches made each day are completely unique, and 70% of searches lie outside of Google’s Keyword Tool. While this suggests that the large majority of your search queries will have received only a handful of clicks (making trend-spotting extremely difficult), it also presents a great opportunity for identifying new keywords outside of the Keyword Tool.

This article will explore the techniques which can be used not only to identify negative keywords from a search query report, but also identify new opportunities for practical keyword expansion.

Not Enough Data

The main problem with a raw Google search query report is the sheer variety of searches. Each search query has minimal data, making it difficult to spot trends and insights. Suppose we had the following search queries amongst the mass of other search queries in your report:

• holiday paris for winter 2011
• holiday in winter 2011 to paris
• paris winter 2011 package holiday

It is hard spot the opportunity ‘winter 2011′ amongst the noise of the search query report. It is hard to see the wood through the trees.

Something more is needed.

Search Query Aggregation

If instead, search queries were pulled apart into their individual words, and click data was then aggregated based on these individual words, we would be able to make more sense of search query reports. For example, suppose we could now identify the following search query themes:

• holiday
• paris
• winter
• 2011
• package

We can now see that ‘winter’ and ’2011′ are popular themes within our search query report. And by aggregating click and conversion data for these search query themes, we can quickly and easily identify the types of themes which are converting well, and those which are converting poorly.

Similarly, if the word ‘free’ was hidden amongst multiple search queries, it would have been difficult to realise that the word ‘free’ was a drain on your AdWords budget. But being able to look at the aggregate click cost and conversion data for all searches containing the word ‘free’, you could quickly and easily determine whether ‘free’ should be added as a negative keyword.

If you’re willing to hand over your search query data, Query Miner has developed a tool which allows you to see the words which are converting poorly, and should be added as negative keywords.

But search query analysis shouldn’t stop at identifying negative keywords.

Oh no.

The real power of search query is in identifying new keyword opportunities – the 70% of searches outside of Google’s Keyword Tool. Although looking at one-word phrases can be useful for identifying negative keywords, doing so would ignore other words in the user’s search query which may be crucial to determine the searcher’s intent.

For example, suppose you identified the following themes within your search query report:

Aggregating your click, cost, and conversion data for each of these themes would suggest that the words ‘cheap’, ‘discount’ and ‘weather’ are prime candidates for negative keywords, due to their poor conversion rates.

Similarly, such analysis might show that keywords containing the words ‘kids’ or ‘children’ are converting extremely well, and suggest that keywords containing the words ‘kids’ or ‘children’ should be expanded or have their bids increased.

But while this insight may be interesting, it is of little use in helping you expand your list of keywords. Just because searches which contained ‘kids’ or ‘children’ performed well for your existing keywords, does not mean they would perform well if you added new keyword variations of ‘kids’ and ‘children’.

Something more is needed.

Multiple Word Search Query Aggregation

Suppose that instead of analysing performance for each 1-word theme, you analysed performance for search queries containing 2-word phrases:

Looking at longer phrases, you are now able can now better understand the searcher intent. You can now see that the performance of search queries containing ‘kids’ and ‘children’ is not universal among different searches, but instead depends on other words they are next to. When someone searches for ‘with kids’ or ‘with children’, conversion rate is extremely poor, but when someone searches for ‘without kids’ or ‘without children’, conversion rate is very high.

Similarly, with 1-word analysis, you may have jumped to the conclusion that the word ‘cheap’ is a poor-performer, and should therefore be added as a negative keyword. But by observing 2-word phrases which contain ‘cheap’, you can immediately see that not all ‘cheap’ search queries are poor-performers. Searches which contain the phrases ‘cheap vacation’ or ‘cheap holiday’ have in fact performed extremely well; it is only the search queries which contain the phrase ‘cheap flights’ which have converted poorly.

That’s all very interesting…

But while 2-word theme analysis might help you make more reliable observations about your search query themes, especially for negative keywords, it still is rather impractical for identifying tangible new keyword opportunities which can be added to your campaigns. Knowing that searches which contained the phrase ‘cheap vacation’ performed well, does not mean that adding the keyword ‘cheap vacation’ would deliver equally promising results. If you specialised in Paris holidays, you would get all sort of non-Paris visitors. You are once again ignoring the other crucial words in the search query which are essential for identifying the searcher’s intent.

Even carrying out a 3-word or 4-word search query theme analysis, you would no doubt uncover useless phrases such as ‘cheap holiday deals to’, ‘cost package for october’, and ‘in paris april 2012′, which would not be sensible to add as new keywords:

We need a way of highlighting new keyword opportunities which can quickly and efficiently be added to the account.

Something more is needed.

Filters

We need filters. Once we have identified our promising 2-word, 3-word, and 4-word phrases from our search query report, we need to filter them to ensure they contain essential qualifying words.

Exactly what words you will use as qualifiers will obviously depend on the specifics of your individual campaigns, but here I have filtered to only show phrases which contains the words ‘paris’ and ‘holiday’:

I now have a list of sensible 4-word themes which I can add to my campaign as new phrase match keywords. And since each of these new keyword suggestions contain the words ‘paris’ and ‘holiday’, I can be confident that these keywords would deliver highly-targeted traffic.

Conclusion

There is a huge amount of data available to PPC advertisers via the search query report. Although we are seeing tools which help advertisers mine their search query reports for negative keywords, the real gold is in identifying new opportunities for keyword expansion. Being able to do so efficiently and reliably is surely the Holy Grail of search query analysis, and can be the difference between a mediocre and successful PPC campaign.

What techniques do you use to mine search query reports for new keyword opportunities? How do you ensure new keywords are qualified and relevant? Share your comments and experiences below.

Alan Mitchell is an experienced Google AdWords manager helping businesses in Australia increase their return on investment from PPC marketing. To find out how search query keyword expansion can benefit your business, get in touch today for a free consultation.

From a client’s point of view, this is great. There is little risk – agency fees are only payable once sales come in. Guaranteed profit!

From an agency’s point of view, it’s also great. Each extra sale is extra revenue, so an agency which is confident of its abilities to deliver value from paid search is rewarded heavily (and fairly) for their efforts. Performance-related pay creates an incentive for agencies to invest their best resources and expertise into making PPC campaigns a success for their client.

Researching cheaper and high-converting long-tail keywords, restructuring ad groups to improve relevancy and regularly carrying out landing page testing to increase conversion rate become all the more worthwhile when there’s a monetary incentive. If an agency only gets paid when they deliver sales, it is worth their time and effort to deliver sales.

Sounds too good to be true. Client risk is minimal. Agencies which perform are rewarded. Agencies which don’t perform…well they are forced to perform if they are to stay in business.

So you’ve decided you want to give performance pricing a go. But how exactly would a performance deal work? And how should you go about creating one for your PPC agency?

Economics

To see how such performance deals would affect your bottom line, and the bottom line of the PPC agency you’ve hired, we’ll use a similar method to that used in Economics of PPC Pricing: Why the Markup Model is Flawed, and look at the cost and revenue structures for both client and agency.

Let’s suppose Shiny Shoes Corp launched a new range of shiny red golf shoes, which they sold online for $15 (OK, they’re very cheap golf shoes). Sales were stagnant, so in an effort to increase sales of shiny red golf shoes, Shiny Shoes Corp decided to pay a PPC agency $10 for every pair of shiny red golf shoes they sold through PPC. If the PPC agency only sold 10 pairs a month, the client would pay the agency $100 (10 x $10), regardless of whether the agency spent $50 or $5000 on clicks. If the PPC agency were to generate 1,000 sales, the client would pay the agency $10,000 (1,000 x $10) – again, regardless of whether the agency spent $50 or $5000 on clicks.

How many sales will the PPC agency deliver? How much profit will Shiny Shoes Corp make? How much profit will the agency make? Will the agency be incentivised to deliver extra sales? Is $10 per sale a fair amount, or should it be $12, or perhaps $8? All burning questions we can consider with some simple economics.

Look at the green line ‘MC (client)’ in the figure below. MC stands for manginal cost, and shows what happens to the costs of Shiny Shoe Company as sales volume increases by extra units. It’s a flat line, which makes sense – the client is paying the agency $10 per sale regardless of sales volume.

Since Shiny Shoes Corp pays the agency $10 per sale, we can also add in the agency’s marginal revenue (red line), which again is flat. At every sales volume, whether it’s 20 pairs or 2,000 pairs, the client’s cost per sale is $10 and the agency’s revenue per sale is also $10.

We also know that Shiny Shoes Corp sells the shiny red shoes online for $15, so we can add in the client’s marginal revenue. Again, it’s a flat line, since Shiny Shoes Corp receives $15 for each sale, regardless of how many pairs they sell.

Now that we have the cost and revenue structures for Shiny Shoes Corp, we can see what profit they’re making. Shiny Shoes Corp’s profit is the difference between their cost and revenue, which is represented by the green shaded area. The higher the sales volume, the higher their profit. Since Shiny Shoes Corp makes $5 profit for every sale ($15 they recieve from the customer online minus $10 they pay the PPC agency), they would want as many sales as possible!

How many sales will the agency will deliver depends on the agency’s profit, so let’s add in the agency’s marginal costs (red line). The agency’s MC is an upward sloping line, since click costs increase progressively as volume is increased.

Why is it upward-sloping?

Diminishing Marginal Returns

Well, the first few sales will come from cheap clicks from brand terms, such as ‘Shiny Shoes Corp’, as well as highly-relevant long-tail keywords, such as ‘red shiny golf shoes for sale’. Not only are long-tail keywords generally cheaper, but conversion rates for these highly-relevant keywords will also be high, meaning fewer clicks (and therefore fewer click costs) will be needed for each sale. The agency can probably bring in the first few sales for only $1-$2 each.

Once the PPC agency has saturated brand terms and highly-converting long-tail keywords, they are forced to show ads for more competitive, more generic and more expensive keywords, which might not convert as well. The higher cost per click prices and lower conversion rates for less-relevant keywords such as ‘golf shoes’, mean sales might cost the agency $8.

Each extra sale costs the agency progressively more, hence the upward-sloping marginal cost line. Diminishing marginal returns set in.

Now we have all our cost and revenue lines for the agency, we can see how many pairs of shoes will be delivered by the PPC agency, and how much profit the client and agency will make.

After a while, when all profitable keyword opportunities are exhausted, when all that is left are expensive and poorly-converting keywords such as ‘shoes’ and ‘birthday gift ideas’, the the agency will start to make a loss from any extra sales they deliver, where the agency’s Marginal Cost goes above the agency’s Marginal Revenue . At this point, the agency will reduce bids, pause keywords and cut back on sales volume until they stop making a marginal loss.

The agency’s maximum profit is where their Marginal Cost equals their Marginal Revenue, at 5,000 pairs of shiny red golf shoes. Any less than 5,000 pairs (say 4,000 pairs), and the revenue for the agency delivering extra pairs of shoes would be more than their cost of delivering those extra pairs (their Marginal Revenue would be greater than their Marginal Cost), so it would be profitable for the agency to increase volume. Any more than 5,00 pairs (say 6,000 pairs), and the agency would make a loss from these extra pairs (their Marginal Revenue would be less than their Marginal Cost), so they would be better off by reducing volume.

Maximum agency profit is therefore where the agency’s MC = MR, at 5,000 pairs of shoes.

At this point of maximum agency profit (5,000 pairs of shoes), we can see the profit for both client and agency. Looks healthy, right?

Wrong.

At 5,000 pair of shoes, there is a wastage, an inefficiency – what economists call a loss of utility. There is extra profit to be made (dark grey area), but since the agency doesn’t want to make a loss from helping the client achieve this extra profit, the extra profit goes unrealised. This makes model inefficient. There is extra profit to be made, but the model does not sufficiently extract this extra profit the market is offering.

The cost-per-sale model starts to breaks down.

What’s more, with a $10 cost-per-sale model, the fee the agency receives is a poor reflection of their efforts.

The Brand Problem

A good PPC pricing model should be an accurate reflection of the agency’s work and expertise, which is not the case with this $10 cost-per-sale model. The first few sales will be from showing ads for brand searches such as ‘Shiny Shoes Corp’, which require little agency effort and will cost the agency next to nothing. Agency profit will be high.

But as sales volume increases, and the agency is forced to invest considerable time and effort to research new keyword opportunities, agency profit will be relatively low. This and low effort/high reward and high effort/low reward problem might cause the agency to cut back on volume even further, thinking these these extra sales and tiny profit (which are highly valuable for the client) are just not worth the extra effort.

So, to recap, Shiny Shoes Corp’s decision to pay a PPC agency $10 for every sale is inefficient for two reasons:

1. The agency will stop delivering sales when the cost of an extra sale is more than $10, even though Shiny Shoes Corp would not mind paying $11, $12 or over $14.50 for these extra sales.
2. The agency’s fee is a poor reflection of the work and expertise required

Okay, so a set cost-per-sale model doesn’t work.

Separating Brand & Non-Brand

But what about a structured cost-per-sale model, such as below? Shiny Shoes Corp pays the agency only $7 for the ‘easy’ sales (brand terms), and $13 for the more difficult sales. With two different pricings, the fee the agency receives is a better reflection of the value they are adding (great!), the loss of utility is reduced (great!) and the agency now has a monetary incentive to increase sales volume to 6,000 (great!).

Awesome! It’s solved both of the problems above! Right?

Wrong.

There is still a loss of utility (the client can still make extra profit if it received these extra sales for $14 or $14.50). And although the agency is more fairly rewarded for their efforts, the agency’s red Marginal Revenue line still does not follow their Marginal Cost line closely. They are not being paid proportionately for their efforts.

How about a multi-step (or progressive) cost-per-sale model, such as below? Shiny Shoes Corp would pay $6 for the first 1,000 sales, $8 for the next 1,000, and so on.

With multiple pricings, loss of utility is tiny, and the agency is fairly rewarded at all spend levels (notice how the agency’s red MR lien closely follows the agency’s red MC line.) What’s more, sales have increased to 7,000! Great!

Such a well-structured model would be great, and as close to the Holy Grail of PPC pricing as one might hope to get. It’s fair, creates incentives, maximises sales volume and maximises total profit (client and agency).

But just as the Holy Grail is hard to find, so is such as pricing model.

Performance Models Are Difficult

A multi-step (or progressive) cost-per-sale model is great in theory, but in practice such a model might be prohibitively difficult to construct. For a progressive cost-per-sale model to work efficiently, it requires an in-depth understanding of revenues at multiple sales volumes, knowledge of brand strength, seasonality, offline marketing influences, not to mention tracking inefficiencies and bias which might exaggerate or under-report sales volume.

One scenario might be where brand strength and click costs are under-estimated by the client, such as below. Fees set too high, and the agency is over-compensated for their services. The client would make little profit, and would be better off with a percentage of spend or management fee pricing deal.

Another scenario might be where click costs and brand strength are over-estimated by the client, such as below. Fees are set too low, so the agency makes a loss from delivering any sales, and the client will struggle to find an agency wanting to manage their PPC for more than a few months. As they regularly jump from one optimistic agency to another, long-term stability goes out the window and are replaced by extra costs, effort and confusion.

A more realistic scenario might be the one below, where in an effort by Shiny Shoes Corp to closely match click costs to fees, offers a slightly under-priced cost-per-sale structure. At some volume levels, delivering extra sales would make the extra agency profit, but and at other volume levels any extra sales would be at a loss. If the agency was at point B, for example, they would be better off either increasing volume to point C, or reducing volume to point A.

Very inefficient. Sales are vastly under-delivered and nobody wins.

This difficulty in creating a cost-per-sale model and setting it at the correct level leaves the client (and agency) with a difficult decision.

A correctly set cost-per-sale deal would be great for the client, as it minimises their risk (they only pay when sales come in), as well as encouraging the agency to perform. It would also be great for the agency, who are fairly rewarded for investing their time, effort and resources into doing what they do best.

But an incorrectly set cost-per-sale model (such as the three above) could be disastrous. If the agency is making a loss, they will refuse to deliver any sales, which is a waste of time for both client and agency and a massive loss of potential sales. If the cost-per-sale fee is set too high, the client will make only a small profit a would be considerably better off with a set management fee or percentage of spend (markup) deal.

So, if you are a business looking to minimise your risk from PPC, as well as incentivise your PPC agency to perform, should you consider a cost-per-sale performance deal?

Cost-Per-Sale Tips

Firstly, be wary of offering a set fee for every sale. You will pay heavily for the agency to simply harvest the value of your brand, and will find that sales are restricted way below your most efficient point.

Secondly, be careful of offering a multi-step progressive model, unless you have accurate sales and revenue data allowing for seasonal fluctuations, offline marketing efforts and special offers, and are confident (and preferably experienced) regarding likely PPC click costs at a range of different spend levels. If guesswork makes up a large part of your research, a progressive cost-per-sale model might be more trouble than its worth.

A happy medium, especially if you a business new to PPC or cost-per-sale models, might be a two-step cost-per-sale model, which separates brand and non-brand sales. It’s not ideal, but limits the brand / non-brand problem and is relatively risk-free (you only pay for sales so are guaranteed to not make a loss from PPC). It does, however, require a decent knowledge of brand searches and likely PPC click costs, so perhaps only consider this two-step cost-per-sale model once you have collected at least a few month’s worth of brand and non-brand cost and sales data.

And remember, a performance deal does not have to be based on sales. Leads, enquiries, email sign-ups downloads or anything which is a desired outcome for your business can potentially be incorporated into a cost-per-action performance deal. Just make sure you have the performance data to back it up.

Are you a fan of the cost-per-action model? Have you made it work for client and agency? Or does it cause more problems than it’s worth? Share your thoughts in the comments section below.

Next: profit sharing. Does it work? What are its limitations? Coming soon.

 

Alan Mitchell is an experienced Google AdWords consultant helping businesses in Australia increase their return on investment from PPC marketing. For more information on how a strategic approach to PPC can benefit your business, get in touch today for a free consultation.

Long-tail keywords are those low-volume, obscure, infrequently searched-for keywords that turn up in your search query reports. ‘Cheap remortgage for bad credit history’ is one example of a long-tail keyword. ‘Remortgages’ is not.

The theory goes like this:

• Long-tail keywords, en masse, can provide significant search volume (high impressions)
• Long-tail keywords have less competition than generic keywords (lower cost per click (CPC), higher click-through rate (CTR))
• Long-tail keywords are more specific than generic keywords, so ads can be better tailored to match the searcher’s needs (higher CTR, higher Quality Score, less wastage from irrelevant searches)
• People making long-tail searches are often further along in the buying cycle and more willing to buy than people making generic searches (higher conversion rate)
• These lower CPCs, higher CTRs and higher conversion rates mean long-tail keywords can be extremely profitable (lower cost per acquisition (CPA))

So are long-tail keywords all they are cracked up to be? Are they worth all the time, effort and commitment they require?

In short: yes.

Over the course of this article you’ll see exactly how search volume, CTR, CPCs, average position, conversion rate and CPA differs for searches containing different numbers of words, and how long-tail keywords can benefit your business immensely. Using three months of real Google AdWords campaign data, you’ll see that long-tail searches outperform generic short-tail searches on almost every measure, and provide a great opportunity to connect with customers which is generally not being taken by the majority of advertisers.

1. Search Volume (Impressions)

Let’s start with search volume. Do people make long-tail searches in any meaningful volume?

Look at the example below. Although 1 and 2-word searches may be under-represented in the example (the account has a natural bias towards keywords of at least 3 words), it is clear that as the number of words in a search query increases beyond 3, the number of searches made using that that number of words falls.

This isn’t surprising. You would of course expect search volume to drop as searches start becoming obscure and lengthy. It is little surprise that more people are making shorter searches such as as ‘cheap televisions Brisbane’ (3 words) instead of longer searches such as ‘low cost Sony Bravia television shops in Brisbane’ (8 words).

What is worth noting, however, is the power of these long-tail keywords en masse. Added together, searches of 5 words or more accounted for 21% of all impressions. While long-tail keywords may be individually insignificant, a PPC campaign with thousands of long-tails can be a serious source of additional traffic.

Fact: Long-tail searches have significant search volume

2. Click-Through Rate (CTR)

Another common belief among search marketers is that click-through rate (CTR) is higher for long-tail keywords. Their reasoning being:

1. Long-tail keywords have less competition, so there is a higher chance someone will click your ad
2. Long-tail keywords are more specific in their requirements, so you can write a more targeted and relevant ad to encourage the searcher to click

While the first point is perhaps rather tenuous (Google’s broad-matching mechanism often sends long-tail searches to advertisers’ short-tail keywords), the second point is definitely true. If someone searches for ‘cheap Sony Bravia 46 inch televisions’, and your ad mentions the words ‘Sony Bravia’, ’46 inch’ and ‘televisions’, perhaps with latest prices for that model, it makes sense that your ad will be more appealing than a generic ‘Sony televisions’ ad.

Let’s have a look at CTR for searches of different word counts. While searches of 1, 2 and 3 words have a relatively low CTR, CTR appears to increase significantly for searches of at least 4 words. CTR, it seems, is considerably stronger for long-tail keywords.

Fact: Long-tail keywords can achieve a higher CTR, as long as ads are tailored to the search query

3. Cost Per Click (CPC) & Average Position

Many search marketers also believe long-tail keywords are cheaper. They have less competition, fewer people bidding on them to drive up their prices, so CPCs will be kept relatively low.

So are long-tail keywords cheaper than generic keywords?

To answer this question, it is important to bring average position into consideration. Since CPCs and ad rankings are closely connected (a higher CPC typically means higher ad ranking), both average position and CPCs need to be considered together.

First, let’s look at CPCs. For searches of 13 words or more, CPCs do tend to be cheaper. For searches under 13 words, however, CPCs tend to be very similar. A 9-word search query costs pretty much the same price as a 4-word search query. CPCs do fall very slightly as word length increases from 3 to 12 words, but I would hardly call that significant.

Now let’s look at average position (a higher bar represents a higher ad ranking). For 1, 2 and 3-word searches, ad ranking is relatively low, and ads are appearing near the bottom of the first page. As word length increases, however, ads are shown significantly higher. They are appearing in the top positions.

So although CPCs were relatively similar for searches of all word counts, long-tails were often shown in a higher position.

When you think about it, this makes perfect sense. When you set a maximum CPC bid for each keyword, Google will show you as high as possible without going over your maximum bid. If long tail keywords are cheaper, Google won’t necessarily charge you less. It is in their interest to charge you as much as possible, so they will instead keep your CPCs close to your maximum bid but show you in a higher position.

Fact: Long-tail keywords are cheaper for the same ad ranking, or the same price for a higher ad ranking

4. Conversion Rate

So we’ve seen that long-tail keywords have a significant search volume. They exhibit a strong CTR and are often cheaper than their short-tailed rivals. But clicks are no good if people don’t engage with your site or part with their cash. It’s often conversion that really matters.

So are long-tail searches more likely to convert?

Many search marketers seem to think so – their reasoning being that people who make longer, more specific searches have already done their research and know exactly what they want. They are further along in the buying cycle so are more likely to open their wallet.

Let’s have a look at conversion rate for searches of different word counts.

It’s a pretty convincing trend. As the number of words increases, so does conversion rate.

Fact: Long-tail keywords have a higher conversion rate

5. Cost Per Acquisition (CPA)

Finally, what does this mean for CPA, profitability, return on investment (ROI)? Is it cheaper to acquire a customer through the long-tail?

Let’s have a look at the CPA column.

Again, there appears to be a clear trend between word count and CPA. Conversions from long-tail searches seem to be cheaper than conversions from generic, short-tail searches.

And it’s not just one or two conversions which are coming through long-tail searches, either. Remember how long-tails of 5 words or more accounted for 21% of all searches? Well, those 21% of long-tails generated a massive 40.5% of all conversions.

Fact: Long-tail keywords have a lower cost per acquisition and can be extremely profitable

Long-Tails Are Your Friend

As we have seen, the benefits of long-tail keywords are many:

1. Significant search volume
2. Higher CTR
3. Cheaper CPCs (or higher ad ranking)
4. Higher conversion rate
5. Lower CPA

Quite simply, they outperform generic, short-tail keywords on every measure.

Don’t get me wrong, long-tails shouldn’t replace your short-tail keywords. Short-tails, if used wisely, are great for building interest and awareness at the early stages of the buying cycle. Your long-tail keyword strategy should complement your short-tail strategy.

So by all means continue showing on your high-volume keywords – after all, they may be your bread and butter that keep your business afloat. But the next time you work on you AdWords account, spend some time researching relevant long-tail keywords. Try to think what people are actually searching for and use keyword tools to help. Structure your keywords into closely-themed ad groups and tailor your ads and landing pages to cater for these specialised long-tail searches.

Your Moment to Shine

Of course, researching thousands of keywords and structuring them into hundreds of closely-themed ad groups, each with tailored ads and landing pages, is by no means easy. It will take considerable time, effort and dedication, not to mention the many hours of keyword and search query analysis, ad group expansion and ad copy testing once your keywords are live.

But think about your target audience for a minute. They are calling out for someone to meet their needs in a personalised and relevant way. It’s the age of social interaction, and people are sick of seeing generic ad after generic ad. And despite many advertisers claiming they are “doing this already”, consumers are not currently getting a personalised and relevant service (see Relevancy: The Holy Grail of PPC).

If you can be the advertiser who understands your audience using search query analysis, if you can cater for their individual needs with relevant ads and landing pages, if you can be the one who makes a mark in your industry, customers will reward you with their wallet. It’s your opportunity to stand out from the competition. So take it.

Alan Mitchell is an experienced Google AdWords consultant helping businesses in Australia increase their return on investment from PPC marketing. For more information on how a strategic long-tail approach to PPC can benefit your business, get in touch today for a free consultation.