The key to any successful SEO and SEM campaign is utilising data to make the right decisions. It’s imperative to combine and utilise data from these two traffic sources to fill in gaps and create a broader picture. This is becoming ever more important as Google begins to limit data and only provide it to paying advertisers.

This is not an article about the pros and cons of each discipline and why you should use one over the other, there’s too much of that on the web already. This article focuses on when and where you should use both and how you can integrate SEO & PPC in a practical way to enhance both of them.

There are four sections here:

1. SEO & SEM together in the SERP – better together!
2. Campaign timeline: AdWords first, SEO second
3. Harmonising the data
4. Harmonising your activity

---

Love & Harmony within the SERP

Let’s first look at how SEO & SEM interact within the SERP. The following is taken from the new AdWords ‘paid & organic’ dimension report in AdWords, which combines AdWords and Webmaster Tools data. I’ve taken this data from two PPC accounts, one in the web design and SEO industry, the other a medical clinic.

The table below shows click through rates (CTRs) in the SERPs, and how they change when ad listings are shown together with organic listings or when served without organic listings. (Note that I have only included Data from keywords that were displayed in both categories: ‘ad shown only’ & ‘Ad & Organic Shown’)

There are three interesting results:

• When Paid listings are shown by themselves, they have a CTR of 19%
• When Paid listings are shown with Organic listings, then the overall CTR of the whole SERP increases to 26%
• When Paid listings are shown with organic listings, even the CTR on paid listings alone increases to 20%!

The last point is especially interesting, if not confusing. It means that when organic listings are present with paid listings, they cause the searcher to click more onto the paid listing. You would think that if there are more results in general on the page, then paid listings will get fewer overall clicks. The reason behind this result may be due to reinforcement, in that a user sees a paid listing, then scrolls down and sees an organic listing, this reinforces the branding of the company and causes the user to scroll back up and click on the ad that originally incited his or her interest.

The data suggests that the more real estate you have on the SERP the more impressions you make on a searcher and overall you get a higher rate of visits then you would without having that real estate – more bang for your buck so to speak.

It’s important to recognise that my sample size was relatively small. However after I saw this report, I also came across results from a larger sample by SEER Interactive which showed the same effect, albeit more dramatic. The SEER results found that ad CTR alone rises from 5.66% to 18.06% with the presence of organic listings which is a huge increase!

(Note that the SEER results may have included all listings, unweighted, whether or not they were present in both categories. This would seemingly cause a bias due to the larger volume of organic listings. My results only included keywords that fit into both categories, in order to make the results more accurate). In any case, this lends further weight to the argument that reinforcement occurs when there are more listings and CTR increases across the board.

---

Be Clever & Run AdWords First

I always recommend investing in AdWords first. What I mean by this is a properly set up and optimised AdWords account. This should have clearly defined campaigns, with ad groups tightly knit to keywords and relevant ads that are directed to relevant landing pages. A well thought out and implemented AdWords campaign will be more beneficial to you in the beginning because:

Budgets: Small to medium size business just don’t have the budget to smash out on something like SEO in the beginning. In the SEO world today, to optimise your site properly is very costly and results can take three months or more to realise. That’s three whole months with potentially no increase in your company’s goals. Running a PPC campaign will bring visitors to your site, you only pay when someone clicks through. So to start with at least you will get some kind of return and if it is profitable, you can use this to fuel later stage SEO campaigns.

Awareness & CRO – Even if your AdWords campaign is not profitable to begin with, it is still valuable. You still are bringing visitors to your site. Not only will this increase awareness of your company, but also it gives you more data. You can learn how visitors interact with your site, what pages convert better, what keywords perform on what pages. Imagine you invested in a large SEO campaign but your website converted terribly. Even if rankings are strong, conversions may be weak. Low cost PPC will mitigate this risk by giving you an idea at a controlled budget.

SEO Learnings – AdWords is a goldmine for understanding how the search engine values your site. From AdWords you can see:

• How did Google judge your pages?
• Which pages have better quality score?
• Which keywords on which pages have the best quality score?
• How do people judge your pages, bounce rates, exit rates, time on page?

These are all ranking factors. If you can identify issues early, you can fix and help your later SEO efforts. In the next section we are going to explore how to get this data out of AdWords to help with SEO campaigns.

---

Let’s get Harmonising

Once you’ve gathered enough data in your AdWords campaigns, you can begin to look at the numbers and decide where to focus your SEO efforts.

Quality Score (QS) & Cost Per Click (CPC) – These two metrics are very useful. By looking at the QS and CPC for inbound keywords to specific pages we can get important data that Google actually uses themselves to make decisions. (Note that this actual CPC data is better than the keyword tool which, just gives you an estimate). Based on this data we can build up a fairly good idea of

A. How relevant Google deems this keyword to the landing page (QS).

B. How competitive a certain keyword is to target (CPC).

Once we have this keyword data we can then map it to the site itself and decide which keywords to target.

The following analysis will focus on utilizing QS to make decisions. Before we begin you need 3 things:

1. Have google AdWords setup to send visitors to relevant landing pages. Any decent AdWords campaigns should have tightly knit ad groups with relevant keywords & ads targeting the right destination page on the target site. If you haven’t setup your AdWords like this and you are sending all your visitors to the homepage, you can still download this report, however it will be less insightful. (You are also probably not missing your campaigns properly.)

2. Have Google AdWords linked with Google Analytics. Setting this up is fairly straightforward and instructions can be found here.

3. Some Excel wizardry – vlookups & pivot tables.

STEP 1 (Export the Analytics Report):

Once your accounts are linked, log into analytics and navigate to the following section: Acquisition – AdWords - Matched Search Queries. Select secondary dimension: ‘Landing Pages’. Set your date range also to the last 30 days. Then at the bottom of the page, select the maximum number of rows that you can. Then export as an Excel file.

This report shows data broken down by actual search query (‘Matched Search Query’) and landing page. This shows us metrics like how man visits, bounces etc… occurred for each specific query to a specific landing page on your site. In the example above, we see in row 1 that a certain query (that I have blanked out) brought 69 visits to the homepage. This data is especially important now, as this level of detail is only provided for paid traffic coming in from AdWords and not organic traffic. On a keyword level organic traffic will soon be 100% ‘not provided’, but paid keyword data is still available!

STEP 2 (Export keyword data from AdWords ):

Now log in to your AdWords account, navigate to the keyword report (for all campaigns). Ensure that the ‘Quality Score’ column is enabled, if not, enable it by selecting the button ‘columns’, ‘customise columns’ and then next to Qual. Score click ‘add’. Ensure that your date range is the same as for analytics, in this case the last 30 days. Now export as an Excel file as well.

STEP 3 (Export search terms from AdWords):

Within the same keyword report in AdWords, now you need to open a ‘search terms report’. Just above the table, select ‘details’ and then select ‘search terms – all’.

This search terms report shows the specific keyword queries that led users to click on an AdWords ad. Within this report, ensure that the column ‘keyword’ is enabled. Similar to step 2, if it is not enabled, you will need to enable it by selecting ‘columns’, ‘customize columns’, then navigate to attributes and next to keyword, select ‘add’. Then select download to export the report.

STEP 4 (Combining the exports):

You should now have three separate Excel Documents:

• Doc 1: Destination Page export from Google Analytics
• Doc 2: AdWords Keyword report
• Doc 3: AdWords Search Terms report

Firstly clean up Doc 1, to only contain the sheet with the data required in it, this will be sheet 2 ‘Dataset1’. Delete the other 2 sheets and rename the remaining tab to be ‘analytics’

Copy all of the data from Doc 2 into a new sheet in Doc1 and rename the tab ‘KWreport’.

Copy all of the Data from Doc 3 into a new sheet in Doc2 and rename the tab ‘STreport’.

You should now have a Doc 1 with three sheets: Analytics, KWreport & STreport. You can close the other two documents and just work with Doc1.

STEP 5 (Match Up The data):

This step is where it gets tricky, and knowledge of vlookups in excel is assumed. First we will import QS into the ‘STreport’ sheet from the ‘KWreport’ sheet. That way we can match QS to actual ‘search queries’. In the ‘ST report’ sheet, insert a new column after the ‘keyword’ column (Column F). Call this new column ‘QS’ and use a vlookup to match up the ‘keyword’ column in ‘STreport’ with the keyword column in the ‘KWreport’ sheet and import QS. The formula for cell g3 should look like this =VLOOKUP(F3,KWreport!$B$3:$L$527,11,FALSE). Now select the new column ‘QS’, copy the column and paste as values over the top, to remove the formula.

The next step is to import this QS value into the ‘analytics’ sheet from the ‘STreport’ sheet. On the analytics sheet, insert a new column after ‘landing page’ in column C and call this ‘QS’. Now use a vlookup to match ‘matched search query’ column in the ‘analytics’ sheet with the ‘search term’ column in the ‘STreport’ sheet and then pull in QS. Note that here you will may get some values returned as #N/A, so it’s preferable to use an iferror formula to return a 0 instead of #N/A. The vlookup should look like this: =IFERROR(VLOOKUP(A2,STreport!$B$3:$G$2229,6,FALSE),0). Similar to before you should now copy the new ‘QS’ column and ‘paste as values’ back in the same spot to remove the formula.

The ‘analytics’ sheet should now have: ‘search queries’, ‘keywords’, ‘QS’ and other analytics metrics. We can now see the actual query, what page this query takes the user to and the quality score Google has given your page for this query. This is a great moment!

Step 6 (Making sense of this data!):

Now that we have the data we need to understand it. This requires knowledge of pivot tables, which is assumed.

Select the data in the ‘analytics’ sheet and insert a pivot table in a new sheet.

The pivot table should be setup to have ‘landing pages’ as rows with values being: ‘Avg. of quality score’, ‘Sum of visits’, ‘Avg. Bounce Rate’, ‘Avg visit duration’. You should also include ‘matched search queries’ as a second row level, to drill down further: The setup will look like this:

Clean up the pivot table, collapse all the rows, filter out any pages that are not relevant and make the values no more than 2 decimal places. Then sort by QS – largest to smallest.

In the results, I like to use conditional formatting in order to quickly see which pages present the best opportunity. Your output should look something like this:

The pivot table shows us valuable insights. We see that the Fiji page has the highest average ‘Quality Score’. This means that Google see’s Fiji terms as very relevant to this page. You can also click on the + on that landing page and view the exact terms bringing traffic to this page. We see that it is worthwhile optimising the Fiji page and we can determine the exact terms that are working, bounce rate for this page is quite high, so this is an area we can work on. Conversely you can argue that because the Fiji page is doing well already, therefore SEO efforts should be focused elsewhere.

Looking further down the list, the yellow fever page stands out. It has a large volume of visitors, yet its quality score is low at 5.9. There is an opportunity here for SEO & for PPC to add more yellow fever related terms to bring up the quality of this page in Google’s eyes.

(On a side note, another useful piece of information that could be added in here is also monthly search volumes from the Google keyword tool. This can be easily included again using vlookups.)

The other way to use this pivot table is to drill down into each page. When we open the plus on the Fiji landing we get the following:

I have sorted this table by sum of visits and we can see that different phrases have various Quality Scores. I can quickly and easily pick out phrases with high volumes and see the ‘QS’ or how well Google thinks they relate to the page. For example, ‘immunisations for Fiji’ has a much higher QS then ‘vaccinations for Fiji’. QS is also higher for longer tail queries then for shorter phrases, suggesting perhaps that Google thinks this page may provide the answer to this query.

This can be thought of as a keyword mapping - research document. It allows us to quickly select a page on the site and decide which keywords are the best to use for optimisation. We can then utilise these keywords within key positions such as the title tags, header tags or within the text itself. The beauty of this is that you are essentially using Google’s own data about the quality of a page to make decisions!

Step 7 (Using a Normalised QS):

Although the following really should be included in your analysis from the beginning, I’m adding it as another optional step because it is already a complicated process, about to get more complicated! The above data is only accurate to a degree and really we should use a normalised (weighted) quality score rather than an average quality score. As Brad Geddes mentions, “averages lie”. Using an average QS, as we have above is not entirely accurate because it doesn’t take into account that many identical queries occur more than once and should have more influence on the QS then they do. If a specific Fiji query has many identical instances with a lower quality score it will only be counted once, but in a weighted system all instances will be counted.

To account for this, in your ‘analytics’ sheet, add a new column that is QSxVisits (Quality Score multiplied by visits). Create a new pivot table this time with ‘sum of QSxvisits’ and ‘sum of visits’ in the values section. Then manually next to the pivot table, create a new column that is sum of ‘QsxVisits’ divided by ‘Visits’. This column is your normalised or ‘weighted’ QS. The resulting table will look like this:

We see that in reality Vietnam actually has a better weighted quality score then Fiji. This presents us with a different and more accurate picture of keyword relevance.

---

Harmonising your Activity

PPC for link building – SEO is more and more about content. Creating and sharing great content is an awesome way to promote your site. However you may often find although you build it, they still haven’t come. Using paid ads to spread this content is a great low cost way to promote your content to a large amount of users that would never see it otherwise. Facebook for example, is a relatively cheap solution. With paid content promotion you are bidding on long tail, non-commercial keywords, this should be relatively cheap. If your content is good, people on social platforms that are browsing cool and useful things may enjoy it and share it, especially if enough people see it. So use PPC to promote your SEO!

Bidding on Brand – I’ve found often that bidding on your brand is worthwhile, even though you may rank first for the term in SEO. This ties in with the first section of this article. It’s often better to have a double listing within the SERP, as it gives your brand more real estate and creates more reinforcement. Organic listings may get less clicks, but overall you will get more visits and probably a higher overall CTR because of reinforcement. And hey, branded searches usually have a strong conversion rate and very low CPC. More visits usually leads to more profit, so bidding on brand is probably a good idea.

Where SEO fails, PPC can help – Think of PPC in this sense as a backup. SEO is not an exact science and will often fail you, it is difficult. PPC can be used as a short term solution when this happens. The keywords that are worth money, but don’t rank organically are the ones you don’t want to miss out on. PPC and SEO can work greatly together if you know where your strengths are in each one.

---

Conclusion

I have tried to show that SEO & PPC work well together in many ways. They cooperate within the SERP to give a better overall CTR. Utilising AdWords as a starting point is a responsible and intelligent way to inform a data driven successful SEO strategy. We’ve explored advanced methods to extract this data from AdWords and take Google’s own quality measures and use them as a guide for an informed SEO strategy, as well as other ways they can be practically and effectively combined. These two traffic sources are cut from the same cloth and by neglecting one of them your overall strategy will be lacking.