This is part one of a six part series about measuring the return on investment of public relations.

As the recession has really taken a stranglehold over the last eight months or so, there has naturally been a renewed interest in public relations' return on investment.  The incentives for the PR industry are clear, as money has drained away from advertising at an alarming rate, there is a real opportunity to channel some of that budget towards forms of marketing that are more cost effective.  For example direct marketing did very well out of the last recession because it could demonstrate its effectiveness both in terms of targeting and in its response rates. But there is the rub, many of us anecdotally feel that PR is cost effective but how do you prove it. 

One of the problems with PR ROI is its very definition.  At its most basic level ROI is a ratio between the profit generated from an investment and the cost of the investment itself. 

As venerable London Business School Fellow Tim Ambler has demonstrated in his paper ‘ROI is dead, now bury it!’ this basic bit of maths leads to some big problems.  According to this definition the best way to maximise ROI is to spend no money since anything divided by zero is infinite.  It would therefore follow that we immediately cut all marketing budgets back to nothing, stand back and watch as the economy pulls sharply out of recession and grows at a phenomenal rate…or maybe not.

So maybe we should look to a more general definition of ROI as what to I get for the money that I invest.  That’s the easy bit, but how do we work out what the ‘R’ actually is. 

Over the next five posts we will look at some of the methods that are used to calculate PR return on investment. 

Next: Advertising Value Equivalents

The posts have been published in reverse order, contrary to blog protocol, so that they read as a consecutive series of articles as you scroll down the page

This is part two of a six part series about measuring the return on investment of public relations. 

Advertising Value Equivalents

The method of placing a value of editorial coverage based on what it would have cost if it were advertising is and old and increasingly discredited one.  However it remains the most popular method of demonstrating ROI.  A feature in last week’s PR Week demonstrated its continued widespread use while Metrica’s soon to be released ‘PR Measurement, Research and Planning in the UK’ research shows that the percentage of PR professionals who use AVEs has increased from 28% to 49% over the last decade.

The appeal of AVEs is that they are relatively easy to work out and they give a number with a pound sign in front of it.  The problem is that it is not showing any form of return, it is merely showing how much advertising would have cost if were in the same place (which it wouldn’t be) at rate-card value (which it wouldn’t be). 

The rise of online content makes life difficult because online advertising works in a very different way from print advertising.  In print the same ads appear in the same place in every copy of the newpaper or magazine.  Ad-servers mean that this is very much not the case for online sites.  As a good example, try refreshing The Sun’s homepage a number of times and see that different adverts are displayed while the content remains the same.

AVEs are also causing problems as the advertising industry is hit.  Trying to place a value based on something that is in sharp decline is probably not a good idea.  Plunging ad rates are leading to much lower AVE figures even though the quality of coverage may be just as good.  We recently had a client who, for historical reasons, used AVEs to report to their board.  Unfortunately their AVE totals fell by over 50% despite their volume of coverage more that trebling over the same time period.

The following four posts will show some credible alternatives to AVEs as a way of demonstrating the ROI of PR.

Next: Part 3 – Cost of Reach

Previous: Part 1 - Introduction

This is part three of a six part series about measuring the return on investment of public relations.

Cost of Reach

This is part four of a six part series about measuring the return on investment of PR.

Market Research

This is part five of a six part series about measuring the return on investment of public relations. 

Correlation with Business Outcomes

We have talked about ‘out-takes’ but what about ‘outcomes’?  We got the coverage, we changed people’s attitudes but did they then go to the website, call our call centre, walk into the shop, sign up for the trial or buy that iPhone?  There are a number of approaches that can help with this.  First and most simply we can plot a media analysis metric (say favourable coverage) against our outcome (say website visits).  We may feel this shows a correlation, but can we prove it, can we quantify this?

 

Luckily, if you have Excel, there are a couple of easy functions that can help.  CORREL() and PEARSON() both effectively do the same thing which is to give you something called the correlation coefficient.  The correlation coefficient is a number that goes from -1 to +1 that shows the strength of a correlation between two sets of data.  +1 is a perfect positive correlation (as one thing gets bigger the other thing gets bigger), -1 is a perfect negative correlation (as one thing gets bigger the other gets smaller) with zero being no correlation.

 

The correlation coefficient while showing a strength of correlation, doesn’t show how statistically significant it is.  The significance is a function of the correlation and the number of data points (which is why more data points generally gives better results).  There are a couple of advanced functions in Excel will provide this information, but it is also available from statistical textbooks and websites.

 

There is a danger with using this type of correlation work to analyse data over time.  The maths behind the analysis assumes that two points in time are totally independent of one another when in reality this is not true.  In the graph below we have an advertising campaign where the sales always spike two weeks after the adverts.  The correlation in this case would be close to zero.  By shifting the advertising forward by two weeks the correlation becomes close to one.

 

 

Advertisers have got around this problem by introducing the concept of ‘ad-stock’, where the effectiveness of an advert declines with a set ‘half-life’ over the following weeks.  In the example below the advertising has a half-life of two weeks.

 

 

 

Correlation work on its own can work in simple situations where PR is the major factor affecting an outcome.  Unfortunately in many real-world situations, things are more complicated where there are many factors at play from multiple marketing activities through to effects from pricing or seasonality.  To this we need to look at econometrics, the subject of the next post.

 

Next: Part 6 – Econometrics

 

Previous: Part 4 – Market Research

 

This is part six of a six part series about measuring return on investment of public relations.

Econometrics 

Even in a complex example of an outcome being affected by many factors there are tools that can help us.  These generally come under the heading of ‘econometrics’.  Econometrics techniques have been around for a while - as a discipline it was founded in the late twenties by Nobel prize winning economists Ragnar Frish and Jan Tinbergen.  The bit of econometrics that is relevant to ROI is known as market mix modelling which uses statistical techniques to disaggregate the various effects including splitting out the influence from different forms of marketing.

By doing this it is possible to work out the percentage contribution of a marketing activity to an outcome, say sales, and therefore to a financial return – the magic R.  If we know the cost of each activity, the I, then we can establish the comparative ROI

Econometrics has proven to be a very popular technique to prove ROI for advertising.  It has been notoriously hard to prove that advertising works ever since Philadelphia retailer John Wanamaker said “half the money I spend on advertising is wasted; the trouble is I don’t know which half” back in the 1860s.  Econometrics has gone someway to answering this question which is why many advertising agencies back up their work with econometrics and a number of larger advertising groups own their own econometrics companies.

This is both an opportunity and a threat to PR.  The opportunity is that many organisations are already developing econometric models.  The threat is that it is often driven by advertising or broader marketing and PR is often not included.  The problem with this is that models are very sensitive to the data that they are given – if there is no PR data then none of the outcome is attributed to PR.  Even if that hard won editorial coverage may well have influenced your audience to act, the model will attribute all of that to those activities that are included.

As an illustration of this Metrica had a client recently whose advertising planning company had built an econometric model without including PR.  Not surprisingly none of the outcome (in this case web traffic) was attributable to PR with advertising taking claim for a significant proportion – 18%.  We rebuilt the model with PR included.  This time the model showed that 8% came from PR with just 10% from advertising.  In the earlier model the traffic that should have been attributed to PR had been attributed to advertising.

The moral of this story is that PR practitioners should act to find out what modelling is already underway in their organisations and make sure that their work is included.

Incidentally in the example mentioned, web traffic was in turn directly related to income.  Because of this it was possible to calculate that PR’s 8% contribution was responsible for delivering £5m.  The PR budget – nowhere near that.  How’s that for return on investment!

Over the past six posts we have looked at a number of techniques to measure ROI.  While AVEs continue to be by far the most popular within the industry we have shown that there are a number of alternatives from the relatively simple (cost of reach) to the more advanced (correlation and econometrics).  All of these alternatives are commonly used by other marketing disciplines, so surely it makes sense that if PR is going to compete at the top table that it uses a similar approach.

Previous: Part 5 – Correlation with Business Outcomes