The Great British Workforce Revolution 2015

Great British Workforce Revolution 2015

Great British Workforce Revolution 2015 Website

I have just agreed to participate in this year’s Great British Workforce Revolution conference. The conference takes place in London on 3rd June and is organised by Angel News. The conference is targeted at non-executive directors, interim managers and angel investors.

I spoke at the 2013 event and have been asked back to discuss the value in independent directors utilising social media to network in order to find work or business leads.

The keynote speaker for the event is Ros Altmann. Ros has recently been awarded a CBE for her services to pensioners. From 2010 to 2013 she was chairman of over-50s specialist Saga.

Details of the conference, including how to book a place can be found here.



SEO Ranking – A Correlation Study

I have decided to publish some data based on an in-depth study of SEO ranking factors in the UK menswear category. The study uses recent data from a variety of sources. These include, and SEMRush.  Rather than just pure ranking I have used actual estimates of organic search volumes. This volume is taken directly from SEMRush, which estimates volumes by each keyword based on Google’s search volume and estimates a click through rate based on ranking. The correlation study looks at the performance of 10 selected menswear websites and compares them across 11 ranking factors.

The Selected Correlation Factors

Compared to many other studies on ranking factors I have attempted to use less esoteric sources of data. Most of these can be found without a subscription and should accessible to people without a high level of SEO knowledge. The eleven correlation factors and their sources are as follows:

  1. The number of pages indexed by Google
  2. The number of high ranking keywords – SEMRush
  3. Moz Page authority
  4. Moz Domain authority
  5. Total Root links – Moz
  6. Total links – Moz
  7. Facebook Likes – Moz
  8. Facebook Shares – Moz
  9. Tweets – Moz
  10. Google+ clicks – Moz
  11. Google Adwords PPC spend

Correlation Values

Correlation values have been calculated using the “Correl” function in Excel. For the uninitiated correlation values range from +1 to -1. +1 indicates a perfect positive correlation and -1 indicates a perfect negative, or inverse, correlation. A value of 0 (Zero) indicates no correlation. Scores above 0.75, either negative or positive could be considered as strong correlations. Likewise scores below 0.5 could be considered as weak.

A caveat in all correlation studies is that not all correlations are the result of causation. Just because it rains on Tuesdays and Thursday doesn’t mean by naming a day with a T causes it to rain.

The Correlation Results

Each of the correlation factors was tested across the 10 websites in relation to the volumes they achieved. In any event the range of correlation scores ranged from a negative 0.13 to a positive 0.98. The scores were then plotted and ranked. The chart of these results is shown below:

SEO Correlation Factors Mens Clothing

SEO Correlation Factors Mens Clothing

If you click on the correlation factor chart you will be able to see the full sized version.
The surprising result is how at 0.98 PPC expenditure correlates so strongly with search volume. According to this study much stronger than the number of root links (0.75), Domain Authority (0.7) or Page Authority (0.66) as measured by

Against this, towards the other end of the scale, total links and most social media measures, even Google+, are seen to be weakly correlated.

The Line of Best Fit

In order to demonstrate how the data for PPC spend and organic search volume correlates, I also provide a graph. This uses a line of best fit.

SEO Correlation Factors PPC Spend

SEO Correlation Factors PPC Spend

Data Limitation

The first thing to establish is the nature of data accuracy. All the measures used are effectively estimates and are therefore inherently flawed. Each measure used is largely an estimate based on a sample. A collection of samples that themselves are algorithmic. Most importantly, the product that all the correlation factors is measured against is an estimate of organic search volume as provided by SEMRush. As I know from studies of websites where I have access to the real figures, the SEMRush data can be wildly wrong. However, the SEMRush data is based on accurate rankings taken from the data base. Secondly alternative  sources of data, say using Majestic rather than Moz as a source of link data or website authority, may provide alternative values and therefore correlations. That all being said, all sites in the study are treated equally. If there is a systematic error in any one measure, then that error is applied equally across all sites.

Market Power and Brand Strength

The last error is perhaps the most obvious. Are we comparing a comparable set of websites? When you study the “Line of best fit” chart you will notice that the PPC expenditure behaviour of the ten sites can be clustered into distinct four groups. One site spends zero. Four websites spend up to £20k per month. Two sites between £30 and £40k. And two large sites spend between £95 and £120k. In my opinion the spread of PPC expenditures is effectively a surrogate for business scale and market power.

Based on a wider analyses of all of these factors, perhaps market power, or brand strength is the real determinate of rankings and therefore volumes. In the case of the UK menswear market, a bricks and mortar retail network, a presence in above the line marketing channels, digital PR, CRM and email marketing activities are what is effectively being measured. If you were a challenger brand up against an online retailer such as Tesco or Marks and Spencer would you expect to outspend and outrank them with your limited budgets and resources. Having a large PPC budget may be a reflection of how well your perform commercially. Logically, if you perform well in organic search you could create the financial resources to invest in PPC activity. So PPC becomes the product of the correlation analysis, rather than the other way around.

At the moment all of the market power factors identified in the above paragraph are outside of the scope of this present study. However, I shall return to them in a future study.


Search Marketing and Customer Engagement

The aim of search marketing is to engage customers. To attract them to your website and develop their interest. Once the web visitor is engaged you have the opportunity to persuade them to undertake an action such as complete a purchase or make an enquiry.

The easiest and most profitable way to attract a website visitor is to own a strong and relevant brand that delivers brand based searches. Whether the method is paid or organic search, brand based searches have the highest propensity to convert.

Widening the Zone of Customer Engagement

Widening the Zone of Customer Engagement

Depending on your business’ scale and standing your brand may not generate large volumes of online searches. And secondly, brand searches are not the only way to attract profitable customers. Specific searches closely related to your products and areas of expertise will also yield profitable interactions. And it is in this area of search marketing activity where effective SEO and PPC Management will yield the best results.

The Customer Engagement Matching Process

  1. Match brand relevancy and saliency to customer product and service needs.
  2. Match your communication and persuasion efforts to the information needs of customers.
  3. Ensure that your website, and other marketing collateral, is consistent with and renders well on the devices and media used by your target customers.
  4. Ensure you understand how your customers utilise search.
    When, where and how? How search interacts with other elements of the communication mix.

By matching your search and digital marketing activities to those of your chosen customers, you widen the zone of customer engagement. At Simply Clicks our aim is to assist you in making this process as straightforward and effective as possible.

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