Posts Tagged broad match

3 Advanced Strategies to Extract New Keywords from Your Google AdWords Search Query Data

Posted by Alan Mitchell in Techniques on October 11th, 2012

So you’ve realised your current Google AdWords strategy is missing out on a big opportunity to connect with long-tail searchers who are further along in the buying cycle and more likely to convert. You’ve also realised you’ve collected a wealth of search query data while you’ve been running your current Google AdWords campaigns over the past few months or years. You therefore want to use your search query data to improve your long-tail targeting, reach these searchers at the later stages of the buying cycle, and increase your return on investment (ROI) from Google AdWords marketing.

However, when analysing your search query report, it can all too often be overwhelming. It can be hard to know where to start. You find yourself falling victim to analysis paralysis, and give up without making any tangible improvements to your campaigns. So to help mine your search queries for new long tail keywords, below are 3 techniques I find incredibly useful:

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Modified Broad Match – How To Increase AdWords CTR and Reduce CPCs

Posted by Alan Mitchell in Techniques on October 19th, 2010

Back in July, after 2 months of successful beta testing, Google rolled out a much awaited improvement to their often notorious AdWords broad match. Modified Broad Match – or the Broad Match Modifier – allows Google AdWords advertisers to place plus signs in front of their keywords to better control the types of searches which trigger their ads. Since every word in the keyword which contains a preceding plus sign must be included somewhere in the user’s search query, modified broad match provides advertisers with an extra level of control over the search queries which trigger their ads.

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.

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The Broad Match Generator

Posted by Alan Mitchell in Techniques on May 20th, 2010

Google AdWords gives pay per click advertisers a wealth of tools to create, test and optimise highly-targeted pay per click (PPC) campaigns. One of the methods of doing so is through match type: exact, phrase and broad.

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 ROI.

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The 10% Clicks Rule Part 3: Does It Work?

Posted by Alan Mitchell in Techniques on July 22nd, 2009

Welcome to the final part of the Clicks Rule special.

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?

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The 10% Clicks Rule Part 2: Process

Posted by Alan Mitchell in Techniques on July 21st, 2009

Welcome to part 2 of the Clicks Rule special.

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.

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The 10% Clicks Rule Part 1: Overview

Posted by Alan Mitchell in Techniques on July 20th, 2009

Welcome to the first of a 3-part Clicks Rule special.

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.

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