To answer the question, it is assumed you don’t just want to know what the end date is for replacing all PPC traffic but the intermediate points to which SEO traffic is achieved given some rankings will take less time than others and some referral traffic from links will be available as soon as the link is granted and published.
The exercise will use PPC data as it is the channel most closely resembling the users for SEO in that they both use the search engines to find products and services.
Why? – PPC data also uses data sets which are transferrable such as ad position. Other channels such as display ads may also use ‘ad position’ however unlike search, the ads are not shown alongside each other. Thus the nature and data of PPC lends itself well to SEO projection studies. Although PPC users are more likely to be ‘buyer ready’, this doesn’t preclude SEO users from converting well (which may and can often outperform PPC on occasion).
a. the client site has no substantial site architecture issues that require attention such as:
Unnecessary confusing meta directives at page level
Slow page loading times on large high PageRank sites
b. PPC Ad position is assumed to be the maximum position available for SEO given the Quality Score of the relationship between the client’s site page content, the keyword being bid for and the bid price. To some extent, it may be an indication of how well the client converts for this keyword given that most clients won’t pay a higher price for a higher ad position if it doesn’t yield cost effective conversions.
c. Links obtained from outreach activities will yield traffic – this is important as part of the KPIs for a successful SEO campaign must include referral traffic from links. Such referral traffic is an indication to the quality of the link as well as the visitors. Referral traffic from links must also be incorporated into the SEO KPIs.
d. The PPC landing pages are indexed in the search engines. If not, the crawlable and indexed SEO landing pages possess similar if not identical content and would therefore achieve (bar chronological history) similar levels of Quality Score if used for a PPC campaign.
Using PPC data, I would extract a report using 30 to 90 days worth of data using the following fields:
- Ad Group
- Avg Ad position
- Avg Cost Per Click
- Conversion rate
SEO is obviously keyword driven hence why keyword is included. Ad Group allows us to see which keywords relate to each other closely as a good Ad Group has a set of keywords that have a close semantic relationship with the landing page and the ad copy.
Impressions shows us the opportunity whilst clicks is an SEO validation that the site has the content to push through the Organic listings.
We also include spend, NOT because that will dictate the amount of spend allocated to buying links on this keyword BUT due to the amount of resource that would be dedicated to finding/creating content for that set of keywords in that AdGroup i.e. you could create the content and publish it on the client’s blog to earn the links required. The content on that post would link back to the landing page you want to rank.
Using the data, create additional column fields:
- SEO Competition (sites with All In Title matches in Google)
- Current Rank in Google
- Estimated Time
- AllinTitle multiplier
- Revised Estimated Time
Before populating the 3 newly created fields with data, you may want to save time by reserving (and eliminating for now) keywords that have had less than 30 clicks in a 30 day period. The reason you reserve and don’t eliminate the unwanted analysis data is because it merits attention as to the opportunities being lost.
For example, you may have a keyword that has 10,000 impressions but no click through, from an SEO point of view perhaps there is content that needs to be created to answer a question that frequently gets asked in the buying cycle. Perhaps landing pages and widgets need to be created at a later date?
All in Title searches can give a healthy metric as to what the competition is for SEO as it is a measure of what webmasters are targeting for SEO. For example a search for “double glazing” reveals 3.6 million sites but an allintitle search (allintitle:”double glazing”) shows 906,000 results which is more representative and discounts words on a page. It also much better than trying to look at the median links on a page as that is on the tip of the iceberg to attempting to reverse engineer the Google system of algorithms which is a fools activity.
Current rankings tell us the starting point and therefore affects the timescales to which the SEO rankings may be achieved.
Estimated time – this is the most subjective field in that it has an ‘it depends’ answer. The dependencies include the competitor response to a loss in rankings, the latency of the SEO content to be crawled (i.e. cache dates of the home page and the content page for promotion). However, we have allintitle matches which whilst imperfect, is probably a factor of these variables and simplifies the analysis, so instead use a ranking table that uses the following profile:
rank time to target achieved
6 – 10 2 weeks from link published
11 – 20 4 weeks
21 – 30 6 weeks
31 – 40 8 weeks
41 – 50 9 weeks
51 – 60 10 weeks
61 – 70 11 weeks
71 – 80 12 weeks
81 – 90 13 weeks
91+ 14 weeks
A competent SEO that has a decent site architecture, landing page content and the budget to work with should be able to achieve all the rankings in 6 months even if it is poker related, hence why nothing is longer than 14 weeks allowing for the multiplier to double the time to 6 months.
Some keywords will be more competitive than others so this is where allintitle matches somes in. The Allintitle multipler could be normalised as shown in the following table:
Allintitles Normalisation Multiplier
906,000 20 =(normalistion value/median)
By normalising the data, you arrive at a set of relative competitiveness between the keywords. This may not reflect the true extent of the SEO competition however. So the median value could have a Multiplier taken as ‘1′ which the rest depending on the allintitle matches will vary according to competitiveness.
Using a vlookup reading the allintitle matches, you can start populating the main sheet with the multiplier and get a revised estimated time.
By this point, you will have the estimated time frame to which you start:
a. projecting the amount of SEO traffic in month1, 2 up to month 6
b. drawing graphs of SEO traffic coming in and PPC traffic being phased out over 6 months
c. drawing graphs of SEO and PPC spend over the next 6 months