Estimate future ROI from SEO efforts.

What NetBiz SEO can do for you?
The simplest possible formula that can be used to predict the ROI for proposed SEO campaigns looks like this:

Predicted ROI = (Anticipated revenue from SEO efforts) – (Proposed cost of SEO project)

Using the above formula NetBiz provides you with an estimate ROI by:

Predicting Future Search Behaviour
In a website, Content is always the King. After having done the keyword research and found best keywords for your website, we use these keywords in building compelling and useful web page content. Users know good content when they see it and if they like it they may refer to other users. This may be through blog posts, articles, e-mails, forums and social media services. Good quality web page content always helps drive more and more traffic to your website. This also helps you in achieving better search engine ranking thereby rendering the best return on investment.

What NetBiz SEO can do for you?
There are many keyword prediction tools but the primary tool used by our team is WordTracker, which provides an estimate of daily searches for specified terms. However, we would like to clarify that is not the most dependable prediction, nevertheless, it can act as a guideline for many general terms. Some account managers choose to ignore these numbers, especially when analyzing SERPs for terms and finding multiple paid search competitors that are bidding exact or standard match instead of broad match. If there are people bidding on a long tail term, chances are that it drives traffic, regardless of the fact that WordTracker may claim zero searches per day in its predictive function.

There are other more robust keyword estimators, a category known as "competitive intelligence tools," such as Keyword Max, Trellian, Hitwise, and qSearch from ComScore. It would likely be a wise investment to buy a license for one or more of these products should you attempt to predict ROI for a proposed SEO campaign. The more predictions you use to develop an average, the more accurate your number of predicted searches will be.

Using paid search reports has proven to be one of the most reliable forms of determining high-value terms to target for SEO. Unfortunately, not all clients will have the luxury of running full-exposure budgeted campaigns for a significant length of time to gather the amount of data needed, especially for waves of searches for products or services that ebb and flow with the seasons.

Another thing to consider is that after the discovery phase, some of the unidentified long tail terms may end up getting ranked, thus driving conversions. These rankings should rightly be considered a result of the SEO campaign, even though all terms were not identified in advance. Thus, padding should be added to the potential aggregate ROI in order to improve accuracy.

Predicting click through rate
It is difficult to assume a click through rate. The possibility of additional listings for the same site within paid or local results, affects its actual position in the top ten, etc. changing the click-through rate dramatically. Without established rankings and a track record of click-through percentages, there may be a large gap between predicted CTR and actual CTR. Simply taking an average CTR for the number one through ten results on the first page of the SERP may be the only solution for this part of the equation.

Hence, it is wise to consider researching aggregate CTRs for websites that are maintaining rankings in the top ten. This is possible if the paid search impression data for the particular term is available and compared to the referrals from organic listings for each of the same keywords. If we do this for a statistically valid sample, we could probably come close to predicting CTR based on actual position within the top ten.

Predicting value of Conversions
Some conversions are more valuable than others. In the case of an eCommerce site, should a conversion that yields a $100 sale be considered more valuable than a conversion yielding a $10 sale? The obvious answer to this question is "yes." This brings us back to the choice of predicting ROI on a per-keyword-phrase level versus an aggregate prediction, which would force assumptions of how many $100 conversions were achieved versus $10 conversions. We could base this on an average sale, but may end up short-selling ourselves.

If a site's conversion event is a signup for a newsletter or an insurance quote, the site owner needs to assign a value to each visit. Again, this is difficult, as some searches are more likely to yield conversions than others. Using an insurance lead as the example, the same search for "health insurance Philadelphia" could yield a family of four buying the best available individual plan, or a single person buying a low-cost health plan.

Once again, an arbitrary estimate would be required for the average sale. The insurance example is even harder to predict due to the fact that some clients signing up may stay with the broker for years, continuously increasing the ROI from that one lead. Others may drop the plan and its commissions after just a few months. There are probably many other similar scenarios that could skew predictions based on a highly variant lifetime value of the client.

In the case of sites that do not have an online conversion mechanism, we can't overlook the branding factor in discussions of ROI derived from SEO. This is particularly important and would require a complete analysis on its own merit.

Identifying Competition
We identify and research web site competitors us to estimate the degree of difficulty in attaining top ten rankings. With in depth understanding we invest time in solid research that provides more or less an accurate estimation of the difficulty involved in pushing the site in top ten.

Considering latent Conversion
The idea of an "assist" exists, where someone may search a more general term and find it organically, early in the buying cycle, and then end up searching a branded term and finding a paid listing, converting on that. This is similar to the leaky bucket theory. Should half or more of the credit be given to the organic result that the visitor first found, or even other results found within subsequent searches, that reinforced your brand?

Hence, in order to combat the major problem of uncertainty of most data sets and inability to determine the actual ROI over the life of a website, following variables are used in order to predict the ROI. Following is a list of variables that are considered to predict RIO:

We started with the following formula:

ROI = (Anticipated revenue from SEO efforts) – (Proposed cost of SEO project)

Breaking this down further, we have:

(Anticipated revenue from SEO efforts) = Conversions derived from Organic search visits

The unknown and known variables that can help solve the formula are:

Obviously, there is a lot of research that goes into predicting ROI of future SEO campaigns.