Last week venture capitalist Bill Gurley published a post called On the Road to Recap.

Would recommend that all of those in the Unicorn ecosystem, or those considering it, read this. Times are changing: https://t.co/VRKOCTB1UZ

— Bill Gurley (@bgurley) April 21, 2016

For anyone who doesn’t know, a Unicorn in this context is a startup company with a valuation in excess of $1bn.

The post analysed in depth the current investment situation in relation to Unicorns and concluded:

“The reason we are all in this mess is because of the excessive amounts of capital that have poured into the VC-backed startup market. This glut of capital has led to (1) record high burn rates, likely 5-10x those of the 1999 timeframe, (2) most companies operating far, far away from profitability, (3) excessively intense competition driven by access to said capital, (4) delayed or non-existent liquidity for employees and investors, and (5) the aforementioned solicitous fundraising practices. More money will not solve any of these problems — it will only contribute to them. The healthiest thing that could possibly happen is a dramatic increase in the real cost of capital and a return to an appreciation for sound business execution.”

The post lit a fire in the VC and startup communities.

In fact Lissted ranks the post as the most significant piece of content on any investment related topic in the VC community in the last two months. 

So I thought I’d see how it compares to other recent posts about Unicorns.

Comparison with other “Unicorn” content

I searched across the last month for posts with the most shares on LinkedIn (URLs listed at the end). If you search across all platforms you end up with very different types of unicorn!

Having found the Top 10 articles on this basis, I then looked at the number of distinct members of Lissted‘s VC community on Twitter who shared each of the articles. The community tracks the tweets of over 1,500 of the most influential people and organisations in relation to venture capital and angel investment.

Finally for completeness I also looked at the number of distinct Lissted influencers from any community who tweeted a link to the piece.

In the graph the engagement numbers have been rebased for comparison, with the top ranking article for each measure being set to 100.

The difference in reaction by the VC community and influential individuals in general is considerable.

15x more influential members of the VC community (169) shared ‘On the Road to Recap’ than the next highest article (11 -Topless dancers, champagne, and David Bowie: Inside the crash of London’s $2.7 billion unicorn Powa).

9x more influencers across all Lissted communities (419) shared the post (46 for the Powa piece).

VC Community reaction examples

Influential retweeters of Bill’s initial tweet above included Chris Sacca, Om Malik & Jessica Verrill.

Examples of key community influencers who tweeted their own views were:  

there is so much truth being told in this post. it is gold. https://t.co/HSQxAzddJd — Fred Wilson (@fredwilson) April 21, 2016

quotable @bgurley: “Being private does not mean you get a free pass on scrutiny.” On the Road to Recap: https://t.co/S4gElFmP08 @500startups

— Dave McClure (@davemcclure) April 21, 2016

Best recap of current private investment climate and unicorn ecosystem I’ve read to date. Must read https://t.co/vWucGRs9Ur via @bgurley — Jeff Weiner (@jeffweiner) April 21, 2016

And people are still sharing it days later:  

In case you haven’t read this post from @bgurley yet – lots of great insights. On the Road to Recap – https://t.co/0WkAETpxeI — Christoph Janz (@chrija) April 26, 2016

Mythical measurement

So, the next time you set out to find influential content, don’t get too carried away with big engagement numbers. Focus on understanding where and who that engagement came from.

That way your conclusions will be legendary, not mythical.

If you’d like to get a daily digest of the influential content in the Venture Capital community, sign up for a free Lissted account here, then visit the Venture Capital page.

Articles

1. Forget unicorns — Investors are looking for ‘cockroach’ startups now

2. What investors are really thinking when a unicorn startup implodes

3. On the Road to Recap: | Above the Crowd

4. Next Chapter: Cvent Acquired for $1.65 Billion

5. The fall of the unicorns brings a new dawn for water bears

6. Why Unicorns are struggling

7. Oracle just bought a 20-person company for $50 million

8. Silicon Valley startups are terrified by a new idea: profits

9. Topless dancers, champagne, and David Bowie: Inside the crash of London’s $2.7 billion unicorn Powa

10. 10 Startups That Could Beat a Possible Bubble Burst

A survey by Cision has found that time spent using social media for work by the UK journalists who responded has fallen. The focus this finding has received is unfortunate as this reduction may simply be due to increased productivity. Meanwhile, for the first time the same survey found that a majority of UK journalists now think social media use for work is both necessary and beneficial.

Cision have produced their annual survey of how journalists are using social media. The top finding is a fall in the proportion of UK journalists using social media for work for four hours or more per day. The level has reduced from 24 per cent in 2012 to 13 per cent in 2014. The inference drawn is that we’ve reached a point of “saturation”, or even decline, in the use of social media by UK journalists.

The thing is, time spent is only relevant if you can relate it to a set objective. In this case the reduction in time seems most likely to me to be due to improved productivity in the use of social media by journalists.

Here are a few potential reasons for this:

– According to the survey, Twitter is the No.1 tool used by UK journalists (75 per cent). Our analysis of when UK journalists joined Twitter suggests they have had between three and six years to become proficient at it.

– Productivity tools are likely to be widely used by now, particularly by those who use social media the most. An example of this is in the survey where it highlights 25% of respondents saying they use Hootsuite.

– Knowledge from earlier adopters will have been shared with colleagues who joined later. Journalism.co.uk’s excellent newsrewired conferences are an example (the latest of which was yesterday).

Meanwhile the same survey also tells us:

– 54% of journalists who responded couldn’t carry out their work without social media (up from 43% in 2013 and 28% in 2012).

– 58% say social media has improved their productivity (up from 54% in 2013 and 39% in 2012).

If the survey is representative, this means a majority of UK journalists now think that the use of social media for work is both necessary and beneficial.

Isn’t this the real story?

Its an interesting tool for identifying the articles, and related topics, that have generated the most reaction in different groups.

It also provides the basis for a few other observations:

LinkedIn Publishing Platform content ranks very highly

In three groups – Students, High-Tech and Health & Pharma – the top ranked article is one that has been published on LinkedIn’s own Publishing Platform.

8 out of the 10 groups have at least one LinkedIn article in their Top 15 and in the case of Students, C-Suite and Marketing more than half of the Top 15 are from LinkedIn.

Only the Automotive and Financial Services groups have no LinkedIn articles in the Top 15. An opportunity there for someone?

In total 49 out of the 150 results are from LinkedIn (there are a couple of duplicates in there). I haven’t had the time to count the results for all the other individual sources but a quick scan suggests that none of them have more than 10.

17 shares are enough to trend in Automotive

The table below shows the number of shares on LinkedIn as a whole that the articles ranked 1st and 15th (the lowest position shown) in each section have received.

I assume the tool’s ranking is based (sensibly) on shares by members of the specific section e.g. Health & Pharma, concerned. This explains the instances shown in orange – IT Decision Makers and Financial Services – where the 15th placed article has received more shares overall than the 1st placed.

This must be because less of their shares were within the specific section being evaluated e.g. the 15th ranked article in Financial Services must have received less than 47 of its 297 shares in this specific section or it would have to outrank the 1st article.

The interesting takeaway for me is that the more specific groups – High Tech, ITDM, Health &  Pharma, Automotive, Financial Services and VC (with the exception of Marketing) – all require less than 500 shares across the entirety of the 270million+ members in order to rank in the top 15. In Health & Pharma, VC and Automotive it’s less than 150.

In a measurement context therefore a piece of content in any of these areas that is receiving tens of shares would appear to be significant.

US content dominates

All of the top ranked articles are from US sources and a quick scan of the others in each section suggests this is the case across the board. No great surprise given that US members are the biggest group at around 30% of the total.

Articles checked for share stats

Students

1st How to Answer Stupid Job Interview Questions
15th How To Become A Jedi Knight

C Suite

1st 18 Things Highly Creative People Do Differently
15th Confidence. Conviction. Charisma: The Art of the Sale. 

Small Business Owners
1st 18 Things Highly Creative People Do Differently
15th 5 Hashtag Tracking Tools for Twitter, Facebook and Beyond 

Marketing
1st Behind the Preplanned Oscar Selfie: Samsung’s Ad Strategy
15th 5 Business Goals of Content Marketing

High-Tech
1st Big Data: The 5 Vs Everyone Must Know
15th Is Microsoft telegraphing the demise of Windows Phone?

Health & Pharma
1st Saying Goodbye to the Old World of Healthcare
15th A Third Of Nursing Home Patients Harmed By Their Treatment

IT Decision Makers
1st How to Build Trust as a New IT Executive
15th 6 IT Strategies to Stay Ahead of Data Center Trends

VC
1st New York VC Investments Top $1B In The First Quarter
15th The Top Venture Capital Investors By Exit Activity – Which Firms See the Highest Share of IPOs?

Automotive
1st First Times Drive: 2015 Audi A3 e-tron plug-in hybrid
15th Hyundai Revamps Sonata That Upgraded Carmaker’s Image 

Financial Services
1st Employee’s Whole Life at-a-glance
15th Should I Rent My House If I Can’t Sell It?

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.

We are effectively looking at three areas:

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?

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 suggest 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?

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.

The transparency of the Online Media World has brought with it greater opportunities to observe and measure the impact of PR, and often at a much lower cost than the equivalent offline measurement.

At Measurement Camp last week (which was great by the way, just wish it wasn’t a 600 mile round trip!) I was struck by the fact that though there was some *very* good work presented there were no pound notes in any of the resulting measures.

In my experience (and for those real experts out there please correct me if I am wrong!) PR measurement often seems to focus on the following four areas: activities, qualification, indicators and actions.

These are all important and useful measures of performance and they allow us to build models to further refine our evaluation, but the one thing they still don’t “measure” (or perhaps quantify is a better word?) is Value.

Value needs to be stated in pounds – or dollars, euros etc depending on your country of origin  It is only in doing this that actual return on investment can be calculated and PR’s true worth to an organisation estimated.

Actions should in theory be relatively straightforward to value. Take the simple example of lead generation. If a campaign has resulted in X number of leads the client should (hopefully – tracking depending) be able to supply the PR professional (agency or inhouse) with relevant information about resulting conversion rates and sales values as well as the cost of generating equivalent sales from other means.

This would allow the PR professional to calculate both the sales return on investment generated as well as the relative cost of generating sales from this type of activity.

More sophisticated measurement can also use data from some of the first three sources to help to correlate the observed activities and indicators with resulting actions when the linkage is not as direct as say a website referral.

But what about the situation where the desired response is less tangible and is more about improving relationships and reputation rather than something as direct as lead generation? The first three measures can be used to assist with this but are harder to give a monetary value to.

People try/have tried to value these Activity based measures e.g. Advertising Value Equivalent (AVE), but such valuations aren’t measuring the value that the PR has created for the organisation, rather they are trying to measure the value of the activities that have occurred. These two things are not the same. Also the way that online advertising and publishing works makes any online AVE calculation even more spurious IMHO.

I think some of the answers to valuing these “softer” areas may lie in the world of accountancy and this will be the subject of my next post.