Show me Numbers

Following my post the other week regarding online readership, sparked by some aggressive sales tactics by one of our competitors, I got talking to Andrew Smith of Escherman and we agreed to jointly carry out a more extensive piece of analysis looking at 50 different online news sites.

We selected ten sites each from the following areas – UK Nationals, Business, Marketing, Technology and Consumer. There was no particular selection process, just an attempt to have a reasonably representative sample and we both hasten to state that this is a relatively limited exercise which should therefore be taken with at least a pinch of salt. Particularly since indexed urls have been used as a proxy for content as this can be impacted significantly by site structure (as stated in slide 21), with some sites having sub domains and/or a more complex content directory structure.

However at the same time with the data that is readily available we think it provides some (arguably) valuable food for thought. So after several hours of research, number crunching and graph generation here are the results (I suggest you view in full screen mode unless you have excellent eyesight):

Site data is sourced from Google for the number of indexed urls via the “site:domain” command and from AdPlanner for the traffic data.

I’ve been rather busy lately moving house, hence the lack of posts and even a reduction in my Twitter activity. To get back in the swing of things a quick post about TweetReach. 

Stephen Waddington highlighted this tool to me at the North East CIPR Awards on Friday (congrats to all the winners by the way).  It is pretty straightforward to use.  Put in a term, a url or hashtag and it calculates the following three measures:

Reach – the number of different people who follow people who have talked about the search in some way.

Exposure – how many times someone could have seen a particular reference to the topic e.g. if 4 people have tweeted it who all have a follower in common then that follower will have been exposed to it 4 times but will only count as 1 in the reach figures.

Impressions – the total number of occasions to see (effectively the sum of the “Exposure” figures for everyone “Reach”ed)

Note that the Reach figure measures the number of different people. Assuming this is the case (and I have no practical way of checking this) then this is good stuff as it ensures that duplication in networks is taken care of. It also tells you what proportion of the relevant tweets were retweets or @replies.

So a very good tool in theory for understanding the extent and likely penetration of a conversation. However unfortunately the bad news is that it is limited to the last 50 tweets, unless you pay TweetReach $20 and even then it is limited by Twitter’s API to the last seven days or 1,500 tweets. The seven day limitation also means that you MUST carry out the analysis close to the time of the relevant conversation as you can’t go back historically. These factors weaken its role as a measurement tool significantly unfortunately IMHO.

Perhaps now that Google are indexing our tweets the tool could be expanded?

Interbrand published their list of the top 100 global brands for 2009 last week, Coca Cola maintaining its position at the top for the ninth year in a row. I thought it would be interesting to compare the brand values calculated by Interbrand with the equity values of the companies concerned as it would indicate those companies with the most to lose (and gain) through their PR and reputation management.

The results for some companies are surprising including the banks, JP Morgan and HBSC, and in particular Apple, who it seems is not very reliant on its brand with only 9% of its company valuation represented by its brand value.

Interbrand’s  methodology effectively values the extent to which a brand is able to generate financial benefits due to the superior demand created through the strength of the brand itself and not the underlying assets, expertise etc of the company.

Comparing this brand value with the company’s stock market value effectively gives an assessment of the extent to which the brand itself is the driver of the company’s performance.

The table below shows the top 50 brands in the Interbrand list sorted in descending order by those whose brands represent the highest proportion of their company valuation. (The position figure is their position in the Interbrand list).

Top of this list is the French company PPR who own the Gucci Group and Puma amongst others. These two brands alone are valued by Interbrand at $11.4bn compared to a stock market value today for PPR of $16.1bn (€11bn) i.e. 71% of the company valuation is accounted for by the brand value of these two brands. Another luxury brand that appears high in the list, with 53% of its value accounted for by its two biggest brands, is Louis Vuitton Moet Hennessy.  This doesn’t seem surprising given the importance of brand in establishing luxury items’ worth.

Bottom of the list are the banks JP Morgan and HBSC. Only 5% of their company valuations is accounted for by their brand values. However this is not a credit crunch effect as this figure has not changed much over the last two years. This seems a little strange to me on the face of it as it implies that the banking sector is much more of a commodity market despite the importance of trust and confidence in this sector.

But more surprising still is Apple. According to Interbrand only 9% ($15.4bn) of the company’s value ($165.7bn) is accounted for by its brand. This compares to 25% for Microsoft and 42% for Sony. This implies that Apple’s brand is not considered an important driver of value in the company and yet I would suspect that most communications and marketing people would perceive that the opposite was the case.

I wonder if the majority of the reason why Apple is valued at 32 times its earnings (as of 21/9/09) driven by high expectations of its ability to innovate and design new products now and into the future and not the Apple brand itself?

Anyone else have any theories?

IKEA figures not calculated as privately owned so no stock market valuation available
Equity valuations were as of 21st September 2009
Tickers refer to New York Stock Exchange except where stated
Where currencies have been translated the following rates to $1 were used:

Euro = 0.682
Yen = 92
Korean Won = 1,204
Canadian $ = 1.077
Swiss Franc = 1.04

This post follows on from Part 2 and assumes the reader is familiar with it. Also a warning this post is a little longer than the rest but I hope it is worth it

When measuring PR IMHO too much emphasis seems to be placed on proving *absolute* causality. A piece of PR, results in coverage, which provokes a demonstrable response, which leads to a required outcome. At each stage proof is required. The reality as I mentioned in Part 1 is that this is often unlikely to be possible to do and as I covered in Part 2 lack of proof hasn’t stopped accountants making predictions. 

What is achievable though is demonstrating that causality was likely. Econometric modelling (or Regression analysis) can tell you whether outcomes are likely to be correlated with particular observable activities and they can also tell you the likelihood that these correlations didn’t occur by chance. 

So how do we go about building models that demonstrate value? I will cover one here and more in the final part of this series.

Share Price based 

Quoted companies should, in theory, be the easiest organisations to build a value based approach around as there is a constant real time assessment being made of the value of these organisations – their share price. 

First we track the impact of PR as we would normally, but we do so in as close to real time as we can. Online this can be done as we often know the exact time when something is published, whereas offline this is much more problematic. We then qualify the activities that occur, seeking to focus in on those that are most likely to have been influential. Finally we look for evidence of indicators of influence arising from or within these activities e.g. positive sentiment in coverage about the company. 

Next we use econometric modelling to estimate how much of the movement in the company’s share price over a period of time is explained by these indicators of PR activity and how much is explained by other factors. 

Sounds a bit tricky? Likely to be very expensive? Well perhaps not.  I recently had a demo of a new piece of software called Fin-Buzz that seeks to help PR/IR professionals do this for UK FTSE 100 companies (Note this was a complete coincidence I only found out about it when researching for these posts and neither I nor RealWire have any link to the company that produces it). 

In my opinion the software could be improved through looking at additional sources of coverage, it currently tracks around 100 I believe that they view as key. I would also sugget including the ability to actually build and run your own econometric models that then produce actual values – to save me the time doing the analysis below! At the moment the software only provides evidence that causality may exist, an example of which I have used as the basis of my analysis below. 

But it is still a good start and I will be interested to see how it develops. 

Practical example 

(Note: There is no particular rationale behind choosing this example other than I was tracking Centrica at the time as we had expected to meet them at the Communications Directors Forum).

Acquisition of 20% stake in British Energy by Centrica plc 

Timeline: 

10th May 2009 – Rumours broke in the evening that the acquisition of a stake, thought to be 25% at the time, was going to be announced. http://news.bbc.co.uk/1/hi/business/8042544.stm

11th May 2009 – Announcement made in the morning that stake would actually be 20% http://www.centrica.com/index.asp?pageid=29&newsid=1783 http://news.bbc.co.uk/1/hi/business/8043191.stm

A graph of the change in share price from the day before announcement until two days after looks like this:

From ft.com

The graph shows that the share price of Centrica rose approximately 6% on the day of the announcement representing a change in valuation of approximately £700m.

In order to model how much of the change in share price was potentially explained by PR, and in particular the reaction to the announcement of the deal, the model needs to include detailed data on factors that could explain movements in the share price. For the purpose of this example I have looked at:

- market data – FTSE100 used (did companies in general experience similar changes in prices)
- comparable company (same sector) data – weighted value of the three FT comparables above used (did companies in this sector experience similar changes in prices)
- sentiment measured in media coverage by Fin Buzz

I have then run regression analysis based on the movements in these variables during the month of May. It should be noted that it is a while since I studied Econometrics at University so the experts out there might pick holes in my analysis  

Two models have been produced. One that models all three variables and one that just looks at the extent to which the movements in the share price can be predicted by sentiment alone.

The graph below shows the movement in the actual share price and the share prices that would have been predicted by each of these models (you might need to load the page itself to see clearly): 

You can see that both predictions are highly correlated to the actual share price. In fact the statistical analysis says that the vast majority of the explanation for the movements in the price relates to the sentiment (R²s of 79% and 84% respectively for those who know about these things).

In addition further statistical analysis (t tests and F tests for the statistical experts) shows that there is a greater than 95% chance that movements in sentiment are important in explaining the movement in the share price and that there is only a tiny chance that this relationship is only by chance.

N.B If anyone would like to see the statistical details then just let me know.

Conclusions

The sentiment measured by Fin Buzz across their sources “explains” the vast majority of the fluctuations in the Centrica share price over this period and hence the change in market value of £700m.

The value of good PR to Centrica in this situation was therefore potentially worth millions. We now enter chicken and egg territory. Was there positive sentiment towards the deal because of how it was communicated or because of the deal itself? The answer is probably both. 

Some of the value is likely to be in the deal, but only to the extent that the reasoning, the strategy and the implications were communicated well. One person could have heard the announcement and thought “well its a decent deal but not really convinced” whereas another who had been better communicated with and therefore understood the thinking better might respond “this is a great deal actually”. The impact on value in each case could be very different. 

Finally even if PR only influenced/resulted in say 10% of the positive sentiment this would still have apparently resulted in the creation of an extra £70m of value. 

But perhaps it isn’t necessary to reach a firm conclusion on this to demonstrate the likely value added by PR in this situation. Let’s face it if you had something worth £700m wouldn’t you want to entrust it to the experts?

In part 4 I will cover some other suggestions for how similar approaches could be taken where the organisation is not quoted and also an idea I have for how it might be possible to answer the chicken and egg question. Any input, thoughts, criticisms etc warmly welcomed.

This post follows on from Part 1 and assumes the reader is familiar with it

So how can the world of accountancy help with measuring the value of PR? 

Accountants measure value all the time – giving an opinion on a set of accounts or valuing a potential acquisition for a purchaser, or disposal for a seller. 

In order to value a company accountants use a variety of techniques. Examples include: 

- Multiples of “profits”, where profits can be defined in an alphabet soup of different ways – PBT (Profit before tax), PAT (Profit after tax), EBIT (Earnings before Interest and Tax), EBITDA (Earnings before interest, tax, depreciation and amortisation- phew!) 

- Discounted cash flow models otherwise known as NPVs (Net Present Value) using WACC (Weighted Average Cost of Capital), CAPM (Capital Asset Pricing Model) – yes even more letters! – and other tools to work out the discount factors used.

Despite the complexity involved in some of these techniques they all basically pose the question: 

“How much money (in today’s terms) will owning this company, or a share of this company, entitle me to in the future?” 

What they are all attempting to do therefore is predict the future. 

Unless you are Mystic Meg this is clearly an impossible task. There is no way that anyone can predict the future with any certainty and hence any valuation is almost certain to be wrong. But that doesn’t stop accountants doing it everyday. 

So when you try and predict the future earnings of a company what are the factors that you take account of? 

Clearly there is the current level of profitability as a starting point. You can then go on to consider factors that demonstrate market potential, competitive advantage and barriers to entry such as: 

- Market expectations in the future for that company’s products
- IP the company has or is developing
- Market share
- Potential to improve efficiency and hence profit margins
- Management team and their likelihood to deliver the company’s plans 

Public/Investor relations plays a role in increasing the “value” placed on a company where these sorts of factors are concerned by communicating these areas effectively. 

But in addition to this the key component of a company’s competitive advantage, and hence its ability to make future profits, is the reputation of its brand. If reputation changes then value can be created or destroyed. This is because the change in reputation will affect perception of the very factors that drive value, such as the likelihood of the company exploiting markets, launching new products and the confidence in the management team.

And PR is the custodian of reputation. 

So accountants give opinions and value companies and yet, with the greatest respect to my former colleagues and fellow professionals, probably don’t understand reputation as well as PR professionals. 

What does this all mean? 

Perhaps we need to look at PR “measurement” in a different way. Perhaps we should be looking at how brand values change, share prices move and the changes in profitability of a company’s products and services. We could then try and demonstrate, through a framework, how reputation management and development through PR has contributed to improvements in these areas. This way PR claims the Value of what it has helped to achieve not the activities or even the actions that have occurred. 

In Parts 3 and 4 I will try and suggest some practical ways we could perhaps seek to do this.