And while most pay per click (PPC) advertisers are probably already doing a fair job at targeting a large number of relevant searchers through their existing keyword lists, there are massive opportunities for PPC advertisers who take the time to research thousands more keywords than their competitors.

Let’s find out why.

1. More Impressions

To illustrate the first reason, let’s consider Google’s phrase match for a moment. By bidding on the keyword ‘sony bravia tv’, and setting it to phrase match, you are essentially saying to Google:

“Show my ad whenever someone mentions the word ‘sony bravia tv’ in their search query”.

The job of phrase match is to show your ads for searches that mention your keyword phrase. You might therefore think this will enable your ads to appear whenever someone mentions the phrase ‘sony bravia tv’ in their search query.

Wrong.

Just because you have chosen to bid on the keyword ‘sony bravia tv’, does not mean your ad is guaranteed to show for any search containing the phrase ‘sony bravia tv’. You are competing with thousands of other advertisers for Google’s search results page real estate, and Google can only show a finite number of ads at any one time (10-12).

When deciding which ads to show, Google will display the ads that are most likely to generate a high click through rate (CTR), and those that have a relatively high Quality Score.

So when someone searches for ‘sony bravia 50 inch tv black’, PPC advertisers who have chosen to bid on a keyword close to ‘sony bravia 50 inch tv black’, and are able to display an ad which is relevant to Sony Bravia 50 inch TVs, is more likely to be awarded the chance to appear on Google’s search results page, than your generic keyword ‘sony bravia tv’, which triggers a more generic ad message.

The percentage of impressions your keywords receive for all ‘available’ searches is counted in Google’s Impression Share metric. The higher your Impression Share, the higher the percentage of available searches in which your ads appear.

The crucial point is this – by researching thousands of relevant keywords, all other things equal, you are more likely to show for a greater number of relevant searches. By researching thousands of keywords, your impressions and click volume will increase considerably.

2. Increased Relevancy

The second benefit of having a comprehensive keyword list is increased relevancy.

If you allowed a huge number of very different search terms to match to a single keyword ‘sony bravia tv’, your ad messages will have to be somewhat generic to cater for the wide range of different search terms. Your ‘sony bravia tv’ ad may appear on Google for searches such as ‘sony bravia 40 inch’, ‘sony bravia 42 inch’, and ‘black sony bravia 52 inch’, so your ad needs to be generic enough to be cater for all these very different searches.

On the other hand, if you had separate keywords and ads for ‘sony bravia 40 inch’, sony bravia 42 inch’, and ‘black sony bravia 52 inch’, you can provide more relevant and tailored ad messages to each search requirement. For example, whenever someone searches for ‘sony bravia 40 inch’, your ad message could mention ’40 inch’ and take visitors directly through to the ‘sony bravia 40 inch’ products page on your website. Similarly, if the searcher is looking for ’42 inch’ or ’52 inch’ Sony Bravia TVs, you ads and landing pages can be more tailored to these phrases.

Under a more comprehensive keyword and ad message strategy, click through rates will increase, as your ads appear more relevant to the searcher’s specific requirements. Quality Score will also increase, resulting in lower cost per click (CPC) prices. And since the user journey is more relevant, efficient and targeted, conversion rates are also likely to increase.

The crucial point is this – by researching thousands of relevant keywords, you can display thousands of tailored ads, and realize the benefits of higher CTR, lower CPCs, and higher return on investment.

3. Better Measurement

The third and arguably most important benefit of having a comprehensive set of keywords is better measurement.

Even through your keyword ‘sony bravia tv’ may be phrase matched to searches such as ‘sony bravia tv deals’ and ‘cheap sony bravia tv’, having thousands of different keywords in your Google AdWords campaigns will allow better measurement and analysis of different search terms.

Even if we ignore for a moment the benefits of increased relevancy (point 2 above), let’s see how separating out your keywords can provide an increased amount of insight into how different types of keywords perform.

SCENARIO 1:

In scenario 1 (below), suppose your keyword ‘sony bravia tv’ receives 6,000 clicks and generates 60 sales, resulting an a conversion rate of 1.0%. It’s delivering a good return on investment, so you decide to keep the keyword running without making any changes.

SCENARIO 2:

Now consider scenario 2, where your 6,000 clicks are now spread out over a greater number of keywords. Like scenario 1, your keywords continue to deliver a total of 60 sales.

However, unlike scenario 1, since you have multiple keywords, you can now see exactly where your sales are coming from. You can see that the keyword ‘sony bravia tv deals’ is performing very well, achieving a conversion rate of 1.6%, while people looking for ‘cheap sony bravia tvs’ tend to convert very poorly (conversion rate of only 0.4%).

You can then take these findings, adjust bids and budgets accordingly, and carry out further analysis as to why searches containing the word ‘deals’ perform considerably better than searches containing the word ‘cheap’. Remember – without splitting out your keywords, this would not have been possible.

The crucial point is this – by researching thousands of relevant keywords, your campaign performance data will be spread over a greater number of keywords, allowing more insightful analysis and optimisation. You can filter out poor performers, push high performers, identify opportunities for keyword expansion, and ultimately deliver a higher return on investment for your PPC marketing budget.

Conclusion

When researching keywords for your Google AdWords campaigns, don’t think:

“I only need to add generic keywords such as ‘sony bravia tv’ and ‘sony bravia televisions’ – everything else such as ‘discount sony bravia tv’ and ‘40 inch sony bravia tv free shipping’ will automatically match to my generic keywords”.

Instead, think:

“I need to add as many long-tail keywords as possible, so I can better see how each type of keyword is performing and provide more relevant and tailored ad messages”.

The best campaigns are those that contain a huge number of relevant medium and long-tail keywords, targeting searches containing differing amounts of qualification. The best campaigns are those that are structured across thousands of granular ad groups, so that thousands of tailored ad messages can be presented. The best campaigns are those that aim to maximise relevancy, engagement, and chance of conversion at each stage of the buying cycle.

When you think you have finally created the ultimate Google AdWords campaign, think again.

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.

While this extra degree of control was largely welcomed by PPC advertisers, modified broad match no doubt adds an extra degree of complication to Google AdWords management. However, as we will see from four seperate modified broad match experiments, if modified broad match is used correctly, it can be extremely effective in significantly increasing click through rates (CTR) and lowering cost per click (CPC) prices of Google AdWords campaigns.

Infinite Matching Possibilities

Modified broad match isn’t just the fourth match type. Modified broad match is the infinite match type. Whereas previously it was only possible to match a keyword in three possible ways, with modified broad match it is now possible to potentially match a keyword an infinite number of ways. The only limit to the number of matching possibilities using modified broad match is the length of the keyword itself.

Say you wanted to bid on the keyword ‘cheap hotels melbourne’. Previously there were only three possible ways you could match this keyword – exact, phrase, and broad:

1. [cheap hotels melbourne] – exact match
2. “cheap hotels melbourne” – phrase match
3. cheap hotels melbourne – broad match

Now, with modified broad match, adding plus signs in front of certain words in your keyword forces those words to be included in the search query. As any word with a preceding plus sign must be included somewhere within the user’s search query, it is now possible to better control the relevancy of PPC traffic. However, this extra control means more possible customisation – there are now a 10 possible matching combinations for the keyword ‘cheap hotels melbourne’:

1. [cheap hotels melbourne] – exact match
2. “cheap hotels melbourne” – phrase match
3. cheap hotels melbourne – broad match
4. +cheap +hotels +melbourne – modified broad match
5. +cheap +hotels melbourne – modified broad match
6. +cheap hotels +melbourne – modified broad match
7. cheap +hotels +melbourne – modified broad match
8. +cheap hotels melbourne – modified broad match
9. cheap +hotels melbourne – modified broad match
10. cheap hotels +melbourne – modified broad match

That’s 10 possible matching combinations if the keyword has 3 words, 18 possible matching combinations if the keyword has 4 words, and 34 possible matching combinations if the keyword has 5 words. It doesn’t take long to realise that modified broad match creates a huge number of possible matching combinations – each which triggers its own unique range of search queries.

While these numerous matching possibilities no doubt add extra complication to Google AdWords management, if modified broad match is approached strategically it can be hugely effective in improving Google AdWords campaign performance. Over the course of 4 AdWords campaign experiments on modified broad match, we will see how modified broad match can lead to significant increases in click through rate, while at the same time significantly reducing cost per click prices.

Experiment 1 – Four Keywords

Firstly, let’s look at a small-scale test which was carried out on an AdWords account over the last 2 months. Below are results for a hotel name keyword (broad match), along with 3 modified broad match variations. Each of the 4 keyword combinations were given their own ad group, the same ads, and the same keyword bids. Over the 2 month test period, each keyword combination received over 200 clicks.

While quality score, average position and average cost per click prices were very similar for each of the combinations, click through rate and conversion rate were significantly higher for longer keywords and those with a greater degree of broad match modification. Click through rate rose from 1.36% to 2.99% to 3.81% to 4.65% as the keyword increased in broad match modification, while conversion rate similarly rose from 3.03% to 3.17% to 4.13% to 4.23%.

Although the experiment was on a small scale using only a handful of keywords, and there could potentially be multiple causes of uncontrolled bias which could have influenced the results, the findings strongly suggest that longer keywords with a higher degree of broad match modification achieve better results than shorter keywords with little or no broad match modification. Considering that longer, modified keywords are more specific in their nature, this is hardly surprising.

Experiment 2 – Multiple Keywords

To provide a more comprehensive analysis of the performance of modified broad match, modified broad match was rolled out across two separate test accounts. Again, the testing time period was just over 2 months, and each test account received over 2,000 clicks. While different keywords had different bids, largely due to their differing levels of competition, care was taken to ensure each match type variation of the same keyword had the same bid.

In test account 1, exact match performed significantly better than the other match types in terms of click through rate (CTR). Phrase, broad and modified broad match had similar click through rates, although average cost per click prices were much lower for phrase match keywords. Although there was little difference in CTR between broad and modified broad match, modified broad match had a 10% lower average cost per click, and a Quality Score comparable to exact match.

In test account 2, however, the story was much more conclusive. Exact match was this time the worst performing match type in terms of click through rate, while Quality Score of exact match was considerably lower than the other match types. Modified broad match had a higher click through rate than standard broad math, although average cost per click prices were slightly higher. However, once again, modified broad match boasted the highest Quality Score, suggesting that modified broad match keywords were perceived as highly relevant for the searches they triggered.

While both test accounts provided results which were largely promising for advocates of modified broad match, the differences in match type performance between the two accounts suggest a more investigative analysis is needed.

Experiment 3 – Amount of Modification in Keyword

In experiment 1 we found that although the sample size was small, keywords with more broad match modification tended to perform better than keywords with less broad match modification. To test the accuracy of this finding, keywords across the two test accounts were grouped according to the number of plus signs they contained. A keyword which contained 4 plus signs for example, meant that those 4 words must be included somewhere within the user’s search query.

Once again, account 1 provided little evidence that more broad match modification resulted in higher click through rates. Although click through rates increased for keywords with 4 or 5 modified words, click volume was significantly lower for these longer words, making it hard to provide a conclusive result. Cost per click (CPC) prices, however, were more conclusive, with CPC prices falling steadily as the amount of broad match modification increases.

In test account 2, not only did cost per click prices fall for keywords with more broad match modification, but click through rate showed a more convincing trend. Quality Scores remained relatively similar across all keyword groups.

Although the results reflect favourably on the use of modified broad match, with keywords having more plus signs generally performing better than those with less plus signs, the results do not take into account the number of words in the keywords which were not broad math modified.

Experiment 4 – Amount of Modification vs. Non-Modification in Keyword

To assess the performance of keywords with differing number of modified and non-modified words, keywords were grouped according to the number of words they contained vs. the number of which were modified. A keyword such as +cheap +hotels melbourne +4 +star, for example, contains 5 words, of which 4 words were broad match modified.

The results show that keywords with a high percentage of their words broad match modified had click through rates considerably higher than keywords where only a few (or none) of their words were broad match modified. While longer keywords also performed better than shorter keywords in terms of click through rate, as expected from long-tail theory, keywords with a higher number of broad match modified words tended to have a higher click through rate.

Similarly, keywords with a greater amount of broad match modification tended to have lower cost per click prices. Keywords with 0 or 1 plus sign were generally expensive while keywords with 3 or 4 plus signs were considerably cheaper.

Although Quality Score was higher for keywords containing a greater number of words, Quality Score remained relatively constant for keywords of varying broad match modification. Quality Score, however, was relatively high across all keywords, suggesting a strong degree of relevancy across the campaigns.

Conclusion

Although exact match was found to perform very well, modified broad match outperformed phrase match and standard broad match in both test accounts. Looking at keywords with different amounts of broad match modification, the results suggest that broad match modification can be incredibly useful in increasingly click through rates and reducing average cost per click prices for Google AdWords campaigns. While keywords containing a greater number of words will naturally tend to achieve higher click through rates and lower cost per click prices, as expected from long-tail theory, the findings suggest that incorporating modified broad match into your long-tail strategy can provide superior results on keywords of all word lengths.

While modified broad match presents a great opportunity for PPC advertisers to improve the performance of their campaigns, it also allows advertisers to increase their control over the types of search queries which match each of their keywords. If modified broad match is rolled out strategically and methodically, with highly-tailored ads closely matching the keywords in each ad group, there is no reason why modified broad match can’t be a stepping stone towards even greater results.

How have you found modified broad match? Did you see similar results in CTR and CPCs? Did modified broad match affect your conversion rates? Share your thoughts and experiences on modified broad match below.

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 modified broad match can benefit your business, get in touch today for a free consultation.

While exact and phrase match keywords are generally more controllable than broad match keywords, broad match can open up your business to a significant number of additional customers – those who might otherwise have been missed if only exact and phrase match keywords were used.

As we consider the pros and cons of each match type, we find that a balance is therefore required between the extra visitors broad match can deliver, and the quality of those extra visitors. In trying to find that balance, we consider a technique called the Broad Match Generator, which uses broad match search queries to generate new exact, phrase and negative keywords. We see how the methodical process of regularly analysing  search query data, to continually expand keyword lists and ad text relevancy (Broad Match Generation), can help take advantage of the opportunities of broad match while still delivering a strong return on investment.

Exact & Phrase Match

Exact and phrase match keywords are typically the most favourable for search marketers, as they allow a high degree of control over the words a searcher has to make in order for their ads to be shown. If your campaign contained the exact match keyword ‘flights to Melbourne’, for example, you can be 100% sure your ad would only appear when someone searches for ‘flights to Melbourne’ exactly.

Phrase match also gives you a high degree of control, and ensures that the words ‘flights to Melbourne’ must be included somewhere in the user’s search phrase. You can therefore be 100% sure you will only receive traffic from searches which include the phrase ‘flights to Melbourne’, such as ‘cheap flights to Melbourne’, ‘flights to Melbourne from Hong Kong’ or ‘low cost flights to Melbourne from China’.

So with exact and phrase match, you have a high degree of control over the search words which will trigger your ads. You can ensure your ads will only be shown on Google for highly-relevant potential customers.

Broad Match

Broad match, however, is not so controllable. Bid for the broad match keyword ‘flights to Melbourne’, for example, and you ads could be shown when someone searches for ‘flights from London to Melbourne’, ‘Melbourne flying club’ or ‘Australian travel deals’. Basically any search term Google believes is somewhat relevant to the keyword ‘flights to Melbourne’.

Not very controllable, you might think, and you’d be right. Why would you risk receiving visitors from people looking for ‘Melbourne flying lessons’, when you can be 100% sure what you’re getting by using exact and phrase matching?

Traffic, stupid!

Broad match isn’t all bad. In fact, it can be incredibly useful. According to Udi Manber, Google’s VP of engineering, 20-25% of search queries each day have never been made before, making it almost impossible to target every potential customer using just exact and phrase match keywords.

No amount of keyword research can predict that someone might search for phrases such as ‘flight prices March 2011 Tokyo to Melbourne’, ‘airlines Melbourne business class from NZ’ or ‘flights around the world via Melbourne’. Broad match can help deliver thousands of additional highly-targeted potential customers, who would otherwise have been missed if only exact and phrase match keywords were used.

So broad match allows you to receive high-quality visitors from search terms you may have missed during your initial keyword research.

But the problem of broad match still remains. Broad match can still send you visitors from hundreds of irrelevant terms such as ‘Melbourne flying lessons’. What a waste of money.

A balance is therefore needed between the benefit of extra visitors from broad match keywords, and the relevancy of those extra visitors. Introducing the Broad Match Generator…

The Broad Match Generator

Since exact and phrase match keywords provide the highest level of control, and allow advertisers to display highly-targeted ads, exact and phrase match searches should account for the bulk of clicks in a paid search campaign. Broad match should only be used as a catch all, to pick up those specific, seasonal and somewhat abstract long-tail searches which were not added as exact or phrase match keywords during your initial keyword research, and as a tool to generate new exact, phrase and negative match keywords.

To see how this Broad Match Generator would work, let’s first look at an example of an excellent user journey.

Example 1 – Exact Match Keyword in Account

Suppose someone searched for ‘flights to Italy from Melbourne’. Also suppose ‘flights to Italy from Melbourne’ exists as an exact match keyword in your Google AdWords account. So when a search is made, your exact match keyword ‘flights to Italy from Melbourne’ is triggered. Not only that, but since the keyword has its own ad group with its own tailored ads, your ad which appears will be highly-relevant and mention the words ‘flights’, ‘Melbourne’ and ‘Italy’, as well as current pricings for the trip. The visitor is then taken through to a landing page which shows details of flights to Italy from Melbourne.

Highly relevant, highly engaging, and likely to result in high click through rate (CTR), high Quality Score, low cost per click prices (CPCs), low bounce rate, high conversion rate and higher return on investment. Fantastic!

Example 2 – Exact Match Keyword not in Account (and search is relevant)

Now let’s see what would happen if a search is matched to one of your broad keywords.

Suppose the search is ‘flights Christmas 2010 to Melbourne’, and ‘flights Christmas 2010 to Melbourne’ is not is your Google AdWords account as an exact match keyword (ignore phrase match for the moment). The search is then matched to your broad keyword ‘Melbourne flights’, and the generic ad for ‘Melbourne flights’ is triggered. The visitor is then taken through to a generic landing page.

Somewhat relevant, you might think, but far from perfect. The searcher explicitly stated they were looking for flights at Christmas 2010, so why not show ads which better answers their question?

This is where the Generator comes in.

For any broad-matched search query, first decide if it is relevant. If it is relevant, then add the search as a new exact and phrase match keyword and give the keywords its own highly-targeted ads in its own ad group.

So the next time someone searches for ‘flights Christmas 2010 to Melbourne’, your ad which will appear will mention the words ‘flights’, ‘Christmas’, ’2010′ and ‘Melbourne’, and take visitors directly through to a Christmas 2010 Melbourne flight page.

Higher click through rate (CTR), higher Quality Score, lower cost per click prices (CPCs), lower bounce rate, higher conversion rate and higher return on investment.

Example 3 – Exact Match Keyword not in Account (and search is not relevant)

But what if the search query is not relevant, such as ‘Melbourne flying lessons’?

Again, this is easy. When you find a search query which is not relevant to your business, add it (and similar irrelevant searches such as ‘instructor’, ‘jobs’ and ‘careers’) as a negative keyword, to prevent it (and similar irrelevant searches) from triggering your ads again in the future.

The result will be reduced wastage, lower bounce rate, higher conversion rate and higher return on investment.

Two Simple Steps to Ultimate Broad Match Generation

The Broad Match Generation process is very simple. On a regular basis, simply look at each of the search queries that have matched to your broad-match keywords, and make one of two improvements:

1. If the broad-match search query is relevant, add the search query as exact and phrase match keywords in their own ad group, with their own tailored ads.
2. If the broad-match search query is not relevant, add the search query as a negative keyword.

Remember, even as you add new exact, phrase and negative keywords, your broad match keywords will continue to match to more and more search terms, so Broad Match Generation is an ongoing process. However, as you increase your number of exact and phrase match keywords, you should see broad match accounting for fewer and fewer of your visitors. A higher proportion of visitors coming through exact and phrase match keywords means you’re more in control of the types of visitors coming to your site and the ads they are shown, and is a sign that your Broad Match Generation is working.

If the Broad Match Generator is carried out regularly, broad match can be extremely effective in helping to target your ads to an increasing number of highly-qualified searchers, while at the same time reducing wastage from irrelevant and wasteful searches.

Broad match should never be used as a long-term ‘set and forget’ keyword targeting strategy; instead, it should only be used to generate new exact, phrase and negative match keywords, and improve the relevancy of your ads. It should only be used as a means to an end – that end being more exact, phrase and negative keywords and better relevancy.

Broad match keywords, left alone, should never be a long-term solution.

Opportunities

As we have seen, ongoing Broad Match Generation is a great way to make use of the extra traffic available through broad match, while at the same time providing a simple and practical means to continually improve the quality of your Google AdWords campaigns. It can help you uncover new seasonal trends and long-tail opportunities (such as ‘Christmas flights to Melbourne’ and ‘flight and hotel packages Melbourne Cup 2011′), and provide you with a great opportunity to provide highly-relevant ads, tailored to these new search terms.

What’s more, since there will also be some difference between your phrase match keywords and the search queries being matched to them, phrase match also presents another great opportunity for similar ongoing refinement. Looking at the searches being matched to your phrase match keywords, and adding new exact, phrase and negative keywords, as well as new tailored ads, can help take your Google AdWords campaigns even further.

And although Google’s recently-announced broad match modifier will help to give you more control over the types of searches being matched to your broad match keywords, ongoing Broad Match Generation will still be an incredibly powerful strategy – not only to help expand your list of long-tail keywords, but also to identify seasonal keywords trends and improve the relevancy of your ads.

Broad Match Generation provides a practical means to continually provide ever more specific and relevant ads to help better cater for the growing demands of searchers and better connect with your target audience. Use it to your advantage and watch how your return on investment from Google AdWords improves.

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 the strategic use of exact, phrase and broad match can benefit your business, get in touch today for a free consultation.

You may remember the 10% Clicks Rule is a technique to help identify the areas of your Google AdWords account which could benefit most from your time and effort (if not, you may want track back to Part 1: Overview and Part 2: Process).

What I want to do now is evaluate the rule using a real AdWords campaign data to assess its viability. Does it work? Does it help PPC management? Does it actually help improve results? Is 10% the right figure?

Example

Let’s start with the example I worked through in Part 2: Process.

As you may remember, we identified the ad groups which were receiving a large percentage of total broad and phrase-match clicks. In the example I used, 4 ad groups received at least 10% of broad and phrase clicks.I then suggested looking at the search queries for these ad groups.This gave me some great insight. Although search queries 54, 183, 55, 56 and 150 were relevant to my products and services, they were being broad matched to ad groups which were not relevant. Looking down the list, I found many similar examples of relevant searches being matched irrelevantly.

So I decided to create 16 new ad groups with 288 new keywords. Doing so gave me ideas of other new types of keywords, so I added them too, some in new ad groups. With these new keywords having their their own tailored ads, I could now be more sure than whenever someone searched for these search queries again, relevant ads would show.

Effects on click distribution

Let’s have a look at the before and after in terms of click distribution:

• The percentage of broad and phrase clicks going to ad group 17 fell from 22.8% to 12.4%
• The percentage of broad and phrase clicks going to ad group 27 fell from 15.8% to 11.3%
• Ad groups 30 and 26 dropped out of the top 5
• Ad group 36 (one of the new ad groups I added with new keyword ideas) moved into the top spot
• The number of ad groups receiving at least 10% of broad and phrase clicks fell from 4 last month to 3 this month
• The amount of broad and phrase clicks going to top 5 ads groups fell from 69% last month to 59% this month

(A more comprehensive comparison of ad group click percentages for both months can be found here).

So although most of last month’s ad groups are receiving a smaller share of broad and phrase clicks, one ad group (36) is now receiving more.

Not ideal, but it’s a step in the right direction. Next month, the search queries for ad group 36 can be analysed and split out into separate ad groups. If we repeat the process a few more times, what we’ll hopefully see is the broad and phrase click distribution spread over a greater number of ad groups.

Effects on actual results

Now let’s look at how overall AdWords results have changed:

• CTR increased by 22.5%
• Click volume increased by 43.2%
• CPCs stayed relatively constant (variation of $0.01)
• Average position of ads rose by 0.6
• Quality Score (weighted average) increased from 7.62 to 7.98
• Conversion rate increased by 33.8%

It seems like the improved ad group granularity, better tailoring of ads and 288 new keywords had a positive effect on CTR, Quality Score and conversion rate. Click volume also rose significantly for the same average CPC.

So great results all round.

More examples

We’ve only looked at one example so far. Let’s repeat the process for few more campaigns to see how the 10% Clicks Rule works on other campaigns.

Highlighted in red are the ad groups which are over 10% and could benefit from some insight.In examples 2 and 3, just looking at the search queries for these highlighted ad groups I found over 300 new keywords that could be added. Most were relevant to my products and services but were being matched irrelevantly.

Although examples 4 and 5 had fewer ad groups over 10%, just looking at the top ad groups helped me uncover some unnecessary broad-matching, suggesting maybe a ‘top 5 rule’ would be better to keep it relative.

Although no before and after results are yet available for these campaigns, it would be interesting to see how CTR, Quality Score and conversion rate improve over time with these ad group improvements.

Conclusions

So what can we conclude from all of this?

• The 10% Clicks Rule made it easy to identify ad groups where time and effort should be focused
• There is evidence to suggest he 10% Clicks Rule successfully helped spread the share of broad and phrase clicks across a greater number of ad groups
• There is evidence to suggest the 10% Clicks Rule helped significantly increase CTR, click volume, average position, Quality Score and conversion rate while keeping CPCs constant

So…if you are worried that too much of your traffic is being broad or phrase-matched, or worried that you are losing control over where your ads are being show, or just want to improve CTR, click volume and conversion rate, this technique could be for you.

I’m convinced of it’s use in helping to improve AdWords campaigns. I use it regularly and it really does help to quickly and easily get to the heart of broad and phrase matching. It saves sifting through mountains of data and becoming overwhelmed with analysis paralysis. That’s just me though – if you’ve tried it out for yourself and have any suggestions, good or bad, I’d love to hear your comments.

Happy optimising!

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 efficient search query optimisation can benefit your business, get in touch today for a free consultation.

You may be familiar with a technique I shared in recent post called the 10% Clicks Rule (if not, you may want to come back once you’ve skimmed through Part 1: Overview). In essence, the 10% Clicks Rule is a technique that aims to improve the relevancy of ads for search queries which have broad or phrase-matched to one of you keywords. Since it is impractical to give every possible keyword or search query its own ad group with personalised ads, the 10% Clicks Rule helps to identify those ad groups which are most likely to benefit from your time and effort.

Part 1 was all theory. What I want to do now is provide a step-by-step guide explaining how to identify those ad groups in your own AdWords account which could greatly benefit from your insight. All we’re trying to do here is run a Google AdWords search query report at ad group level, filter out exact match keywords (to leave broad and phrase match only) and highlight those ad groups with more than 10% of broad and phrase clicks. These are the ad groups we want to look at. So if you’re a seasoned AdWords and Excel pro, feel free to skim through the bullets or jump ahead to Part 3: Does it Work?. For everyone else who might need a little more guidance, continue reading for a detailed step-by-step guide.

Download a search query report

• Log in to Google AdWords, go to the Report Centre and click ‘create a new report’
• Click ‘Search Query Performance’
• Select ‘ad group’ as the level of detail, ‘summary’ as the unit of time
• Select an appropriate date range
• Click ‘create report’, open it once it completes and export it to Excel

Pivot the data

Once we have the search query report in front of us, we want to summarise clicks by ad group.

• Delete anything above the campaigns/ad group/search query row so ‘campaigns’ is in cell A1
• Scroll to the bottom and delete the ‘totals and overall averages’ row
• Select all data and headings
• Go to Insert, click ‘PivotTable’, the ‘OK’
• This should create a new sheet

Calculate clicks by ad group

Next we want to filter out exact match clicks and calculate each ad group’s broad and phrase match click volume.

• Make sure you can see the ‘PivotTable Field List’ toolbar on the right-hand side (if you can’t, try clicking on the blank PivotTable or go to Options > Field List) – your sheet should now look like this
• Drag ‘ad group’ into the ‘row labels’ box – this should list all your ad groups in column 1
• Drag ‘clicks’ into the ‘values’ box and ensure it says ‘sum of clicks’ – this should show click totals in column 2
• Drag ‘Search Query Match Type’ into the ‘report filter’ box which should add a drop-down filter in cells A1 and A2 – your field list should now look like this
• Click the drop-down filter, click ‘select multiple items’ and ensure only broad, broad (session based) and phrase  are ticked – like this

Calculate percentages by ad group

You should now have a list of ad groups with totals of their broad and phrase clicks. Let’s now calculate each ad group’s percentage of total broad and phrase clicks.

• Scroll to the bottom and make a note of the ‘grand total’ number of broad and phrase clicks
• Click anywhere on the PivotTable to ensure it’s selected and click Options > Formulas > Calculated Field on the toolbar
• Type “Percentage” as the name
• Type “= Clicks / total_clicks” into the Formula box, where ‘total_clicks’ is your grand total of broad and phrase clicks you made a note of earlier
• Click OK – this should add a new column with each ad group’s percentage
• Ensure the ‘grand total’ of this new column equals 1
• Change the formatting so that each number reads as a percentage

Highlight high-volume ad groups

Now that we have percentages calculated for each ad group, make a note of those ad groups…

• Right-click anywhere in column 3, go to ‘Sort’ and select ‘Sort Largest to Smallest’
• Make a note of ad groups with more than 10% of clicks

These are the ad groups with a lot of broad-matching and phrase-matching going on. These are the ad groups that could benefit with your time and effort.

The fun part

You’ve now got everything you need to start make powerful changes to you AdWords account. You can stop here and use your own intuition to make improvements to these ad groups, or continue reading for some ideas and suggestions on what to do next.

Search query analysis

• Go back to your original search query report sheet so you can see all your search queries
• In the ‘ad group’ column, filter so that only the ad groups you made a note of earlier are ticked
• In the ‘Search Query Match Type’ column, filter so that only broad, broad (session) and phrase are ticked
• Sort the clicks largest to smallest

Your search query report should look something like this.

Take a moment to familiarise yourself with your search queries. People are typing these searches to find your products or services. You need to decide what action to take. For each of your search queries, you could either:

1. Add it as a negative keyword (if it’s not relevant)
2. Add it as a new keyword in its own ad group (if ads in that ad group are relevant)
3. Add it as a new keywords in a new ad group (if ads in that ad group are not relevant and new ads are needed)

First decide if any of the search queries are irrelevant to your business (option 1). Make a note of any irrelevant searches in a separate Excel sheet – you can add them as negative keywords later.

Great. Let’s now assume that all remaining searches are relevant to your business. You now need to decide between options 2 and 3 – whether to add the search query as a new keyword in that ad group, or in a new ad group.

To decide whether option 2 or 3 would work best, have a look at the ‘ad group’ column for the search query. It is this ad group the search query is being matched to. Open up AdWords Editor and now find that ad group. Look at the ads. These ads are being shown whenever someone searches for the search query. Are they relevant? Do they mention the search query in the heading or descriptions? Could they be improved in any way to increase relevancy, Quality Score, CTR and conversion rate?

If you think the ads are relevant to the search query, add the search as a new keyword to that ad group (option 2). If you think you could write better, more relevant ads for the search query, add the search query as a new keyword in a new ad group and write better ads for it (option 3).

Great rule, but does it work?

Hopefully if you’ve made it this far you’ve managed to have a go yourself and found some juicy ways to improve your AdWords campaign. While I hope you found it simple and straightforward to follow, feel free to share your thoughts and comments.

In the final part of the Clicks Rule trilogy, I look at real AdWords examples and explore how it can actually help improve results of AdWords campaigns. Part 3: Does It Work?

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 efficient search query optimisation can benefit your business, get in touch today for a free consultation.

Here’s the theory

No more than 10% of total broad and phrase clicks in your Google AdWords account should come from a single ad group. If more than 10% of your total broad and phrase clicks comes from a single ad group, the keywords in that ad group are being over broad-matched or over phrase-matched. Too many searches are going to that ad group’s broad and phrase-match keywords, so the ad group could benefit from keyword expansion and search query analysis.

Example

Suppose you found an ad group which accounted for 18% of your total broad and phrase clicks. This ad group is a prime candidate for improvement for two reasons:

1. Ad group expansion

High-volume ad groups are perfect for ad group expansion.

Spitting out the ad group’s keywords into separate ad groups allows you to write more tailored ads for each keyword. Tailored ads are likely to have a beneficial effect on click-through rate (CTR), Quality Score, costs per click (CPC), ad ranking and conversion rate.

Since it is impractical for every keyword to have it’s own ad group (imagine how tedious and time-consuming 10,000 keywords and 10,000 ad groups would be!), the 10% rule highlights the ad groups and keywords that are likely to benefit most from being split out and having their own tailored ads.

2. Search query analysis

High-volume ad groups are also perfect for search query analysis.

Search queries are what people actually type into Google before they click on one of your ads. Running a search query report for the whole AdWords account allows to to assess whether each of your search queries are relevant to your business, and adding them as negative keywords if not.

Running a search query report at an ad group level, is even better. Not only can you decide if each search query is relevant to your business, but you can also decide if each search query sufficiently matches the ads in that ad group. If the ads in the ad group are very different to the search query, the search query could benefit from having its own ad group with its own personalised ads.

So for each broad and phrase search query you found that matches to the 18% ad group:

• If the search query is irrelevant to your business – add the search query as a negative keyword
• If the search query is very close to the ad group’s keywords and ads – add the search query as a keyword in the same ad group
• If the search query is different to the ad group’s keywords and ads and you think it could benefit by having it’s own personalised ads – add the search query as a keyword in a new ad group

Since it is impractical to look at the every ad group’s search queries, the 10% rule highlights only those ad groups which are likely to have the biggest effect for the amount of time you spend making changes.

Broad and phrase only

You may ask why look at only broad and phrase clicks? What about exact match?

Exact-match keywords give you complete control over the user’s search query. Since you can be 100% sure what the user will need to type into Google for your exact-match keyword to be triggered, you are able to write highly-targeted and personalised ads without having to worry about hundreds of different search queries triggering your exact-match keyword. It is relatively simple to look at an exact-match keyword and decide whether its ad could be made more relevant.

However, with broad and phrase match, things aren’t so simple. You could spend all day trying to write perfect ads which closely match your broad and phrase keywords, but ultimately it is up to Google what kinds of searches get matched to these ads.

For example, you could write a highly compelling ‘Cheap Sony TVs’ ad for your ‘cheap Sony TVs’ keyword. However, if the user searches for ‘Bravia 42 inch deals’ and they gets broad-matched to your ‘cheap Sony TVs’ keyword, your ‘cheap Sony TVs’ ad will appear. It will look irrelevant to the user.

A better ad would mention ‘Bravia 42 inch deals’, although this is only possible by creating a dedicated ‘Bravia 42 inch deals’ ad group. You know you can’t create a dedicated ad group for every search query, so where do you start? Where do you draw the line?

This lack of control and uncertainty with broad and phrase match can be a real problem for advertisers trying to create highly relevant campaigns. The whole point of the 10% Clicks Rule is to help regain some control, by providing a technique to help you quickly and easily get to the heart of your broad and phrase matching and make changes that are likely to have a powerful effect. It’s not meant to be a strict ‘rule’ as such, more a ‘guideline’ or ‘rule of thumb’ which I have found to work in my experience.

That’s all for part 1. Comments and suggestions welcome.

In Part 2: Process, I’ll take you through a step-by-step guide to running rule for yourself – finding those ad groups in your own Google AdWords account that could benefit from a little TLC. If you’re more interested in exactly how the 10% Clicks Rule actually works or how it can help to improve your AdWords results, skip to Part 3: Does it Work?

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 efficient search query optimisation can benefit your business, get in touch today for a free consultation.