New Jobs at Onalytica - Recruitment Manager, Training Officer

We have posted some new exciting jobs in our job section today.

Check our job section here www.onalytica.com/jobs.aspx

A Milestone for Onalytica

It has been a couple of months since posted on this blog. I have been really busy with all the things that are exciting when you run a company; developing and delivering services, working with customers and celebrating successes with colleagues.

However, I have some exciting news to share with any readers that are still occasionally checking the blog: We have external investors!

This news marks an important milestone in the company’s history.
In the last few years I have had an increasing number of organisations and individuals approach me with an interest to discuss either investing in Onalytica or simply buying the business outright.

I have not spent much time pursuing these approaches because I didn’t want to take time and attention away from the company’s existing funding source: its customers.

Being funded exclusively through sales is an approach that has worked well for us, because it has forced us to pay very close attention to what customers really want to pay for. It has also ensured that we have not gone completely off on to many tangents that eventually turned out to be less aligned with the needs of customers.

However, I have come to the conclusion that we are now at a growth stage where external funding, together with the experience and attention of external investors, can help us better seize the great opportunities that lies ahead.

I am therefore immensely proud to announce that Onalytica has been offered and has accepted an investment of £5 million from a small group of private individuals.

Although there are likely to be many areas where we will benefit from this investment, I am especially focused on 4 areas:

Firstly, it will help us create an employee share scheme whereby existing and the many new employees we will be recruiting can share in the company’s future successes in a whole new way.

Secondly, it will help us commit more resources to accelerate our product development and to offer our customers even more jaw-dropping insight and competitive advantage.

Thirdly, it will help us service our customers, many of whom have global requirements, in more and eventually all the markets where they operate and are demanding our services.

And last, but not least, the extension of the company’s board of directors will add proven experience, fresh perspectives and personal networks that will be beneficial to all the company’s stakeholders.

So, if you are dreaming of working for a successful, growing, exciting, ambitious and well-funded company; with a stellar client list, have great colleagues and be part of a new and exciting industry, then you should check regularly our jobs section. Alternatively you should simply declare your interest, along with a motivated covering letter (important!) and your CV (also important), in an email to ‘work’ at Onalytica dot com. We are looking forward to hearing from you.

What is the talk about FTSE?

I was looking at the debate in relation to FTSE and noticed how it has changed in the recent months.

The chart below shows the Share-of-Buzz (relative frequency) of seven issues discussed in relation to FTSE.

Notice how ‘Recession’ and ‘Oil’ was about the same in January and how Oil is now by far the dominant topic (of all seven).


The next chart (below) shows the Share-of-Influence for the same topics (still in context of FTSE). Share-of-Influence is similar to Share-of-Buzz but with the important difference that each contribution in the debate is adjusted with the calculated weight of the ‘voice’ that speaks (aka ‘Influence’).

Notice how ‘Oil’ is much more dominant here, highlighting the fact that those who are more influential in the debate on FTSE are more focused on ‘Oil’ than on the other issues.

It’s also interesting to see that the only thing that remained of (almost) constant importance to those with more influence is the focus on the future.

We are hiring

We have updated our vacancy section have new positions for programmers, analysts and a PR/Office Manager.

These are super-interesting positions (well paid too), so if you know anyone who is made of the right stuff, then do them (and us) a favour and pass it on.

See available positions here

Upcoming Events

I will be speaking at the events listed below.

eMetrics Marketing Optimization Summit, 21st of May – Topic: “What's coming next? Measuring Social Media.”

Social Media Influence Conference, 4th of June – Topic: “Measuring Influence and Audience”

Let me know if you’re going and want to meet up.

Predicting Sales from Online Buzz - 2

For several years now, many organisations have been actively monitoring and analysing the online debate in order to gain further insight into consumers’ wants, needs and experiences.

Increasingly, organisations are now taking online analysis a step further by using online buzz to help predict sales, market share and other outcomes, and to detect changes in competitors’ MarCom activities.

The idea is compelling in its simplicity: by listening to what stakeholders are saying about different brands, a reliable forecast can be made as to whether or not customers may prefer one brand over another; and why.

Unfortunately, however, it is not as straightforward as it may sound. Simply counting up the change in brand mentions is not good enough and may often lead to disastrous results.

A crucial element in transforming the online buzz into reliable predictions is the ability to attribute to each online ‘voice’ the correct weight; often referred to as ‘influence’. This of course is very intuitive: It counts more when somebody who is a recognised authority or has a large following on a particular topic talks about a particular brand than if somebody with no following voices his or her opinion. If a particular car brand is mentioned in the driving section of The Times it counts for more than if a competing brand is mentioned on my blog or indeed in The Sun.

Some may now be thinking that surely more sales will only be the result if a brand is mentioned in a positive context or is unreservedly recommended. However, that is not necessarily the case.
All things being equal, it is normally better for a brand to be mentioned in a positive context than in a negative one. But we have to remember that every time a brand is mentioned in a negative context there are two opposing forces at work. The first force is negative. The reader may be slightly less likely to favour the brand because of the negative context. However, because the mention of the brand increases the reader’s familiarity with the brand and brings the brand to the forefront of the reader’s mind, a positive force is at work too.

Whilst the old saying that “any PR is good PR” is not entirely true, research shows that it is, in fact, almost true. Unless the talk about a brand is either very, very negative or unanimously negative, any brand mention is likely to have an overall positive impact. The occasional negative mention actually often contributes positively to increasing outcome.

In fact, when we at Onalytica test prediction models we can see that in most cases we get a better (and very good) prediction of outcome (e.g. sales) if we leave sentiment out of the model. (However, I must stress that in certain situations the model actually improves slightly by including sentiment.)

When we started out predicting sales and other business outcomes from the analysis of online buzz, we were concerned that the data we collected online were not representative of the total debate. However, our ability to satisfactorily predict sales of goods that cannot be purchased or delivered online, i.e. cars, movie visits, and prescription drugs, based solely on analysing the online debate, has largely satisfied these concerns.

In fact, when we collect the buzz online what we get is a very large and very representative sample of the overall buzz (off line and online); when it comes to the debate about the vast majority of interesting issues and brands there is no separate online or offline debate. When there is an increase in the online debate about a brand there is also an increase in the similar debate at the pub and in the work place.

The ability to predict business outcomes from online buzz has sparked new ways of working among several of our clients.

Some now set out targets known as “influence budgets” that are similar to traditional budgets where revenue is the target except that here the target is related to how much online ‘influence’ a brand earns; on its main brand, its individual products and services, and on key marketing messages.

Using “influence budgets”, organisations can now predict more precisely whether or not they are on track to meet their actual revenue or market share targets; and if they are not on target they are in a position to take action earlier.

The actual actions initiated are often more traditional. They most often involve adjusting their MarCom activities, including (but not limited to) the total spend.

An interesting side-effect is that the process of benchmarking brands against an influence budget also gives organisations early insights into changes in competitors’ MarCom spends and their effectiveness.

An overview of predicting business outcome from online buzz would not be complete without a few comments on how some of the key elements differ across markets.

When it comes to predicting outcome from online buzz there are two main factors that differ from market to market.

The first market-dependent factor is the lag from an observed change in the online buzz to the change in business outcome. This lag may range from a week (e.g. prescription drugs) over 30-60 days (e.g. cars) to over 6 months (e.g. white goods).

The second market-dependent factor is how accurately changes in business outcome can actually be predicted. In certain segments where the goods/services are difficult or expensive to sample before purchase (e.g. cars, travel, mobile phone services, gadgets, financial services, etc.) the models work extremely well. In areas such as cheap FMCGs where the goods can easily and inexpensively be sampled, the ability to predict changes in sales may work less well, but can still compete very favourably with traditional models.

In a market place where products and services increasingly are at par, earlier access to better and more precise information is likely to become even more important.

By transforming online buzz into actionable intelligence, managers can now act earlier and on safer grounds if they are not on track to meet their business targets.


(To see an example of the realtionship between sales and online buzz see this previous post.)

Don't Mention the R-Word

Will McInnes has another interesting post today (“Don’t mention the economy”). It got me thinking about how careful many are “not talking the economy into a recession”.

Using InfluenceMonitor I had a look at the debate surrounding the UK economy.

Figure 1 (below) shows how frequent a number of issues appear in the debate on the UK Economy. (Normally referred to as the ‘Share-of-Buzz’).

Notice the increased focus on the “recession” from October to January, followed by a very small drop.

At the same time, the focus on “slowdown” is mostly constant.

Because the Share-of-Buzz is unadjusted for influence (all voices count the same) the picture closely mirrors the debate among ‘the general public’.

Now, notice Figure 2 (below). It shows the Share-of-Influence of the same issues. Because this metric is adjusted for influence it a closer depiction of the debate among the top influencers including the influential media.

Notice how the decline in the debate on “Recession” is followed by a corresponding increase in the use of “Slowdown”.

It’s almost like some omnipresent voice said “Don’t mention the ‘R-word’ – the safer word is ‘slowdown’”.

I am sceptical to what extent you can avoid a recession by not talking about it. You may be able to postpone it a short while, but if your economy is not sustainable, you will be hit sooner or later. The market forces will (thankfully) always catch up.

It may be telling that the “optimism” element has all but disappeared from the influence adjusted debate on the UK Economy.

The Buzz of a Stock Market Crash

(All graphs as of noon GMT January 22nd 2008)

The stock markets took a tumble yesterday (21st of January) but looking at the online buzz it didn’t really come as a surprise.

Figure 1 (below) shows the number of different mentions of FTSE in the last 30 days as well as the aggregated sentiment.

Notice how the sentiment drops sharply on the 14th – a week prior to the big share price crash yesterday.

Figure 2 (below) shows the relative Share-of-Influence of certain words used in the context of FTSE.

(Share-of-Influence is calculated by calculating the relative frequency of each word, but adjusting for the measured topical influence of the stakeholder ‘speaking’. Example: When the debate is about ‘FTSE’, anything published by Guardian weighs approximately 3 times anything published by Daily Mail.)

Notice how ‘Recession’ and ‘Crash’ have increased their presence in the debate in January.

Figure 3 (below) shows the sentiment of the context that these words appeared in over the last 30 days.

Notice that in general, ‘Recession’ has recently appeared in a more negative context than the other words – even ‘Crash’.

Predicting Sales from Online Buzz

The relationship between online buzz and business outcome (sales, market share, subscriptions, etc.) is a topic of increasing interest to many businesses.

The thought is compelling: What if you could listen to the online debate and precisely predict how much you (or your competitors) are going to sell next month or quarter?

Actually, in many cases you may just be able to do that.

Before I move on to a real life example of how online buzz and sales are related I would like to take a step back and explain the rationale for why that relation exists.

The typical way an organisation drives sales is via some sort of market communication; be it advertising, PR or some other form of activity.

In its simplest form the chain works like this: A company runs an advertising campaign. Those who are exposed to the campaign may be impacted in several ways. Some may accept the positive message conveyed while others may just become more aware of the brand and the offering presented. In all circumstances the brand moves up in our attention. We become a little bit more aware of the brand than we were before.

This increased awareness (as well as the message presented) leads to increased conversations about the brand and/or the message. The increased awareness (and the offering) usually also leads to more sales. This, of course is nothing new. If it wasn’t true, the £100 billion advertising, marketing and PR business would be resting on a sham. But advertising actually works – and more often better than traditional models capture.

A practical example may look something like this: A mobile phone operator (let’s call it ‘Mobuzz’) runs a fairly traditional advertising campaign on TV, billboards and online and in doing so exposes hundreds of thousands (maybe millions) to their message.

Even if the campaign is pretty average the very least it achieves is that it gives Mobuzz a little higher mindshare among those who are exposed to it. However it does more than that. It actually impacts those who are not exposed to the campaign as well. It does that via word-of-mouth.

Imagine two friends having a chat. One person, who hasn’t been exposed to Mobuzz’ campaign, tells the other that he is considering changing his phone provider as his contract is coming to an end. The other person may offer some advice or relay some personal experience, but because this person has been exposed to the Mobuzz campaign this person is slightly more likely to mention Mobuzz than if he or she and not been exposed to the campaign. This now raises the awareness of Mobuzz with the person who hasn’t been directly exposed to the campaign and even though the increase in awareness is miniscule this person is now slightly more likely to choose Mobuzz than before this conversation occurred.

If you could listen in on this kind of conversation between friends, you would be able to detect which brands gets mentioned more (and less) in which contexts and thereby start to form an opinion on which brands are gaining more (and less) mindshare. This in turn would be a strong predictor of future sales.

Aside from the fact that the thought of such monitoring is scary (and probably illegal) it is also not necessary if somewhere else we can capture a representative sample of the conversation. Enter the Internet.

Online, individuals, media and other organisations ask questions about brands, discuss them, rave about them and air their grievances. By capturing these conversations and processing them correctly we have, for many – but not all topics, a large representative sample of the conversations.

Now, turning the observed online debate into actual sales predictions is not as straight forward as you may think.

You may think that if there is a sudden increase in the debate about brand A, compared with the competing brand B, this will lead to more sales for A (compared to that of B’s). However, that would be too simplistic.

Very importantly, you have to adjust for the ‘weight’ or ‘influence’ of the voices that speak. If I write a story about Hyundai cars on my blog it doesn’t carry as much weight as if The Times driving section or a blogger with authority on this brand does it.

Therefore, raw buzz monitoring, where all voices are treated with equal importance, is mostly useless to predict anything.

There is a lot of good research to show that the more influence a brand accumulates, the larger share of the market it will gain.

This is intuitive as well: If a greater proportion of the talk is about a particular brand, this brand is going to be at the front of mind of more people. And if those who talk about the brand are voices of influence it is intuitive that it will have greater impact than if said voices have low influence.

In fact, most research I am aware of more than suggests that, over time, relative market share among brands will equate to relative share-of-influence.

Figure 1 (below) shows the percentage change in monthly influence and percentage change in monthly (UK) sales for Nissan Pathfinder for the period of February to July 2007. We can see that the two graphs follow a similar path and they appear to be strongly correlated. In fact, the Pearson product-moment correlation coefficient (a metric often used in PR and Advertising research to measure the relationship between observations and outcome) shows a correlation of 0.99 (the scale is -1 to +1); a very, very strong correlation.

For Pathfinder we can see that the typical lag between earned influence and sales seems to be shorter than one month. This is not always the case but in my experience it is typical for cars that have been on the market for some time and thereby well known to potential consumers.

Figure 2 (below) shows the similar data for Nissan Qashqai. The period here is from March to July 2007 (introduced in February).

At first glance the two variables seem to be less correlated, but in fact the correlation (0.98) is almost as strong as for Pathfinder. There is however, a lag between the earned influence and the sales.

Notice how the change in influence increases sharply from April to May while the change in sales increase slows.Change in influence then falls from May to June, only for the change in sales to follow with a one month lag.

The lag may be caused by the fact that this is a new model. If this is the case then it is likely that the lag will become shorter as more become familiar with the model.

The lag may also be explained by delivery shortages, but regardless of cause, the point is to illustrate that measuring influence is a highly effective way of understanding where the sales are heading.

There is much more to be said about how analysis of online buzz can be used to predict future sales and market share, but I hope the above has raised the awareness of some of the possibilities.

IBM Predicts the End of Advertising as We Know It

Last week, IBM released a report that forecasts “greater disruption for the advertising industry in the next 5 years than occurred in the previous 50”.

The report is really, really interesting – mostly because it is so thorough and comprehensive. I strongly recommend reading it.

Read a summary and download the full report here

I am very interested in hearing your comments/reactions to the report.

Big Brands Connect Directly With Consumers

NY Times has a fantastic article today about how big brands are sidestepping the traditional media channels and connecting directly with consumers:

“We want to find a way to enhance the experience and services, rather than looking for a way to interrupt people from getting to where they want to go,” said Stefan Olander, global director for brand connections at Nike. “How can we provide a service that the consumer goes, ‘Wow, you really made this easier for me’?”

“We don’t automatically think about television anymore,” said Joaquin Hidalgo, vice president for global brand marketing at Nike. “There was a time when brands like Nike could tell kids through the medium of television what was cool, what was in, what was not in, because that was the only window they had into the world. That has completely changed now.”

The article is totally in line with what our clients are telling us and well worth a read

Speaking in Berlin

I will be speaking at the Sales and Marketing in Travel Europe 2007 in Berlin on the 23rd of October.

I am looking forward to presenting some new interesting findings there and also announce a new partnership.

If you’re attending or in town then send me a mail and we can meet up.

UBS takes the attention away from Bear Stearns

I was looking at the debate on the problems surrounding the subprime lending crisis in our InfluenceMonitor service today.

The figure below shows the share-of-influence(1) of a number of well known investment banking brands has in the online “subprime”-debate.



Notice how the share-of-influence of Bear Stearns and UBS seems to be correlated: Initially UBS was the brand in focus. In June however, Bear Sterns announced problems with some of their hedge funds. For a while it took the heat of UBS.

However from July and onwards the focus on UBS has been steadily growing while the interest in Bear Stearns has dropped almost correspondingly.

Interestingly Citygroup, Merrill Lynch, Morgan Stanley, ABN AMRO, Credit Suisse and Deutsche Bank mostly escape attention.

The focus on Goldman Sachs however seems to be growing.

(1)
Share-of-influence is calculated by measuring the share of earned coverage a brand gets in a particular context and then factoring in the measured, topical influence of each voice that discusses the brand. So, when the topic is "subprime" a mention in NY Times will count for roughly 50% more than a mention in CNN.com’s money section.

Halo 3 does the job for Xbox

We have previous (1, 2) written about how Nintendo’s Wii has outperformed Sony’s PS3 and indeed all other comparable games consoles.

Until now the focus has mostly been on the battle between Wii and PS3, but in recent months Microsoft’s Xbox has been making waves.

The figure below shows the relative share of buzz about the 6 major games console brands from June 1st to 23rd of September 2007.

Notice how the buzz levels of PS3 and Wii have been relatively steady while that of PS2 and GameCube has been declining.

Microsoft’s Xbox seems to be the only one with steady growth although it seems to be relatively small.

Tracking share-of-buzz is interesting because we know from research that share-of-buzz and share-of-market converges, so if the present trend continues, Xbox is on route to a small but steady increase in market share.

However, we also know that share-of-influence and market share normally converges faster so it is normally our preferred (main) variable when trying to predict future market share.

(The difference between share-of-buzz and share-of-influence is essentially that the latter includes a weighting of each mention according to the mentioning media’s measured topical influence. When calculating share-of-buzz, all mentions essentially counts the same.)

The figure below shows the development in each brands share-of-influence for the same period.

Notice how much more dramatic the picture looks: PS3 and Xbox are losing and gaining (respectively) share-of-influence much faster than the previous graph would indicate.

This would indicate at least two things: First of all, that the coverage of Xbox more often takes place in media with above average influence on the topic of “games consoles” and similar that the coverage of PS3 is usually in media with below average influence on this topic.

Second, we can predict that the increase in Xbox market share and the decrease of PS3’s similar will be more dramatic, both in terms of magnitude and speed, than the first graph would indicate.

A third observation might be that since Xbox’s increase seems to come at the expense of PS3’s, this might indicate that PS3 and Xbox are fighting for the same audience and are considered substitutes. Those who are considering buying a Wii are more likely to be choosing between buying a Wii and not buying a console at all. If this is true then part of Wii’s success is that it is enlarging the market for games consoles with new customer segments.

Now, we also know from research that if a brand has high share-of-positive-influence its market share and share-of-influence tend to converge even faster.

However, this just makes things even worse for PS3.

The graph below shows the development in sentiment or tone-of-voice of the articles/blogs/forums where each brand appeared in the relevant period.

We can see that Wii and Xbox are at a positive sloped angle indicating that the positive mentions (dramatically) outweigh the rest. PS3, on the other hand, is represented by a flatter curve indicating that the posts on this brand are more balanced (or neutral) and thus on average less positive than the two other main brands.

So this all leads to the question of why Xbox sale is performing so well.

The answer is likely to have several reasons, but look at the figure below that plots the change in debate on Halo 3 and the change in the debate on Xbox for the analysed period.

More specifically the figure shows the change in accumulated influence on a month-by-month basis for Halo 3 and Xbox.

Notice how the lines follow the same trend. In August there was an extraordinary large change in influence for Halo 3 but while it does pull up the debate on Xbox it doesn’t do so with the full force of the change.

The figure below gives a more precise picture of exactly how closely correlated the debates on the two brands (Halo 3 and Xbox) are.

The figure plots the % change in accumulated influence for Halo 3 along the x-axis and the similar change for Xbox along the y-axis. The line is a linear trend line showing the correlation coefficient to be 0.788 which indicates a strong correlation.

Whilst we haven’t proven a causal effect here I think it is at least intuitive to assume that it is Halo 3 that mainly causes the debate on Xbox and not the other way around (although some argument can be made for that).

But if we for a second assume that the causal effect is from Halo 3 to Xbox then we can take our analysis one step further.

We can see from the graph that the elasticity of the relationship is about 0.2 (0.171) indicating that if Microsoft is successful in generating a 1% change in the debate on Halo 3 they are likely to increase the accumulated influence of Xbox by 0.2%.

Because of the strong relationship between share-of-influence and share-of-market the above could be translated into monetary value if we had estimated the relationship between share-of-influence and share-of-market for these brands. However, I don’t currently have access to good market share data for games consoles, so it will have to wait for another day.

Measuring Influence – PR Blogs – Part II

UPDATE: I have discovered that I was a bit too quick with the results listed below. In the process where I manually (step 2) removed a cluster of non-blogs (NY Times, CNN, Time, Advertising Age and other large media properties) who are also often mentioned in a PR/Blog context I accidently also removed a handful of very influential blogs including (at least) Shell Holtz, Bulldog Reporter, Hyku and Todd Andrlik. I was simply not careful enough when I cut out the big media (or non-blog) cluster.

I have therefore decided to redo the analysis from scratch, so a new version should be posted in 2 weeks or so.


In my previous post on this topic I promised to measure the influence of blogs discussing “PR” and “blogs” using citation analysis.

The list appears below but first a few comments on how it was done and how to read it.

How it was done:

1. Using a topical crawl of the Internet, blog posts that discussed the topic of “PR” and “Blogs” in the same article were collected along with blog posts that were sufficiently referenced in this context. (Meaning: If you discuss the topic of “PR” and “Blogs” or being discussed in that context, then you are a candidate).

2. Some blogs, that appeared to be very closely related, were consolidated and some blogs/websites were manually removed because they were not deemed relevant to the context.

3. The posts were analysed for references/citations between them. The citations were extracted and turned into a massive system of simultaneous equations that were solved to provide influence.

4. The influence was normalised to a scale between 1 and 100.

(Many more details can be found in the articles referenced in the Part I of this post).

As influence is a relative measure you read the table like this:

Micropersuasion has (roughly) twice the influence of B.L. Ochman when the topic is “PR and Blogs”; or Top Rank Blog has (roughly) half the influence of Constantin Basturea.

The influence is topical so it is only a good measure when the topic is PR and Blogs. If the topic was, say “PR, Blogs and Measurement” the number (and indeed the ranking) could be expected to be different.

A few comments to the list:

Micropersuasion is clearly in a league of its own. No question about that.

However, Edelman have a large network of employees who run good blogs and while I don’t think they have a deliberate strategy of over-referencing each other, no one can blame the network members for being more familiar with the other Edelman blogs and therefore referencing them a bit more than they might otherwise had done.

You may, if you inspect the list, find bloggers whose position you disagree with. You may think this analysis overrates or underrates them.

If you feel a blog is rated higher on this list than you would expect, it is likely because you are assessing their popularity rather than their influence.

A blog you feel is rated to high is often rated higher because it is read (and referenced) by other bloggers who have above average influence. You could say that such “over-influential” blogs “punch above their (popularity) weight”. Blogs like Into PR, The Blog Herald and Marketing Vox are examples of blogs that are somewhat more influential than their popularity should lead everyone to anticipate.

Measuring Influence – PR Blogs – Part I

In the recent weeks a number of blog posts dealing with measuring influence have stirred up quite a debate.

Jeff Jarvis and Steve Rubel aired their thoughts on the issue.

David Brain and Jonny Bentwood from Edelman’s London office published something termed “Social Media Index” where they propose a brand new method for measuring on-line influence.

Most of my feelings after having read the article were (far better) summed up by Jennifer Mattern in her comment.

The article offers no research, no references to prior research, no logical reasoning for its claims and proposes no way of testing the model.

Can you imagine if the CEO and the Head of Research of a large investment bank published a new options pricing model without actual research and without mentioning the Black–Scholes model? Of course not. So why in PR?

Actually the very notion that influence is not related to a topic is comical. As I understand it, the article proposes that someone has the same influence regardless of the topic discussed. In other words, TechCrunch (for example) is as influential on the topic of fly fishing or jogging as it is on Silicon Valley gossip. I don’t think that’s the case. We know both from intuition and from research that influence is topical.

At best, the Social Media Index is an indication of popularity. But popularity is not influence. Those who are very popular often have good influence but you don’t need to be very popular to have a lot of influence.

When you measure popularity, all “votes” count the same. However, when measuring influence each “vote” counts with the weight of all the votes leading to the voter.

Take a look at the figure below.

Person A is clearly more popular than person B. However, those who listen to person A do not, to any large extent, go on to influence others.
Quite differently so for B. Those who listen to person B they go on to influence others, who go on to influence others, and so on. The aggregated impact (or influence) of B is in this case bigger than A.

The figure (above) indicates why models that only take the first layer into account will come up short when trying to explain the overall outcome.

In pre-Internet times measuring popularity (or “reach” or “circulation”) was a relatively good proxy for influence because those who read a particular news paper or watched a TV programme did mostly not go on to influence anyone outside their close social circle.

But because of the Internet this has all changed and the social event horizon is now defined by language rather than physical distance. Both direct and indirect influence must therefore be taken into account when trying to measure influence correctly.

Relative influence correlates better to outcome than relative popularity simply because influence takes the indirect effect into account.

So how to measure influence?

Well, it’s been done for a long time. In the academic community “citation analysis” has been used for decades to measure the influence of academic journals, articles, scholars and universities.

The principle is quite simple: You collect all references made between articles about a particular topic. The references are transformed into a large set of simultaneous equations that, when solved, provides the relative influence of each journal. Thomson Scientific is probably the leading provider for the academic community.

However, the original science for measuring influence in a linked network was developed by Wassily Leontief who devised something called the Input-Output Analysis. It was originally (and still is) used to measure how sectors of the economy directly and indirectly influenced each other.

Leontief won the 1973 Nobel Prize in Economics for this specific work.

Now, you may doubt that knowledge gained in pre-Internet times more than 60 years ago can provide any useful input to explaining how to measure online influence.

But in much the same way as engineers at NASA draw on Isaac Newton’s work, those who shape the on-line world draw on Leontief’s.

In 1965 Random House published a book by W. H. Miernyk titled “The elements of input-output analysis”. The book deals, as the title says, extensively with Leontief’s work.

This book is cited as a source in the article “Measuring the relative standing of disciplinary journals” by P. Doreian (1988).

Doreian’s article then goes on to be cited as a source by Jon M. Kleinberg in his article “Authoritative Sources in a Hyperlinked Environment” (1998).

Then, same year, an article, which you may have heard of, cites Kleinberg’s:

Lawrence Page, Sergey Brin, Rajeev Motwani, Terry Winograd. The PageRank Citation Ranking: Bringing Order to the Web.

There you have it: From Leontief to Google in 4 easy steps. (There may be shorter/more paths).

Ok, end of part 1.

In part 2: The list of the 80 or so most influential PR blogs measured using citation analysis including their relative influence. Stay tuned.

Positive Word-of-Mouth paying off for Nintendo

Independent has a story today about Nintendo quadrupling their profits in the most recent quarter; mostly due to Wii.

If you look at how the sentiment for a number of brands in the games console space has developed over the last 90 days you can see why Nintendo is doing well. (See below)

The Word-of-Mouth about Wii is just so much more positive than that of the competing brands.

Xbox followed Wii for the first 60 days, but couldn’t keep up. The others were left in the dust.

The sentiment above is adjusted for the topical influence of each voice to give a more correct representation.

See a previous post on Wii and positive sentiment here.

Benchmarking the influence of a blog

Another interesting example of how influence has developed over time comes from looking at the blog of Iain Dale. Mr. Dale is a prominent political commentator whose blog has gained quite a following.

The graph below shows the influence of Mr. Dale’s blog when the topic is “David Cameron”. The baseline is again the influence of the BBC (same context).

We can see that the Influence of Mr. Dale’s blog in February was roughly 8% of that of the BBC.Since then his relative influence (compared with the BBC’s) has grown steadily – until the end of June. Here it took a bit of drop.

However, it is likely that the drop was attributable to a surge in the general influence of the BBC on the topic of David Cameron.

Using the contextual influence of The Guardian as a baseline for Mr. Dale’s blog reveals that he is still doing well. (See below).Benchmarking influence aside it is actually interesting to see how much influence a blog can carry on a major topic. Mr. Dale’s influence on the debate on David Cameron currently stands at about 15% of that of the BBC and just under 60% of that of The Guardian.

Benchmarking Influence

Measuring how the influence of a stakeholder develops over time is a topic of great interest to many of our clients.

Some clients are interested in understanding the effects of a marketing/PR effort. Others may be interested in identifying new rising stars among the influencers.

However, benchmarking influence over time can sometimes be a bit tricky. Because influence is relative we have to benchmark the influence of a stakeholder relative to one or more other stakeholders.

Using InfluenceMonitor I took a look at how the BBC’s influence on the topic of climate change has developed.

As a baseline I used the influence of IPCC, the Intergovernmental Panel on Climate Change.
Figure 1 (below) shows the relative influence of the BBC as a percentage of that of the IPPC since March 1st this year.

The BBC used to be more influential than IPCC on this issue, but around the end of April its influence dropped below that of IPCC. We can see this as the relative influence drops below 100%. Notice, however, the spike in BBC’s influence at the very end of the graph. The increase in BBC’s influence is a good illustration of how a heavily discussed article can dramatically increase influence.

On the 10th of July BBC published an article about a new study that (apparently) concludes that there is no link between the cosmic rays from the sun and global warming. (See partial screen shot below).

As can be seen from the graph below, this article caused a spike in the number of references and inbound links to the BBC, in the context of climate change, over the following days.

We are hiring – please pass it on

I am trying to fill 2 new openings – one for a Media Analyst and one for an ASP.NET/SQL programmer.

Please pass it on if you know someone who might be interested.

The full descriptions are here http://www.onalytica.com/jobs.aspx

No agencies, please.

Nintendo, Sony and Customer Satisfaction

In the December 2003 issue of Harvard Business Review, Frederick F. Reichheld published his seminal article The One Number You Need To Grow.

In the article Reichheld demonstrates that in an industry, those companies that have the largest proportion of customers recommend the company and its products, over time, outgrow the competition.

I immediately thought of Reichheld and his famous article when I read an article in today’s Independent. The article reports that the market capitalisation (total market value of all outstanding stocks) of Nintendo is now bigger than that of Sony, even given the fact that Sony’s turnover is 8 times that of Nintendo.

The article reports that the phenomenal results of Nintendo are largely due to the fact that Nintendo’s Wii is outselling Sony’s PS3 by at factor of 2 or 3, depending on the geographical region.

Add to this that Nintendo’s profitability on the Wii is much better than Sony’s profitability on the PS3.

At Onalytica we track the games console market on an ongoing basis and the sentiment analysis clearly shows that consumers talk much more positive about Wii than PS3.
Figure 1 below shows the distribution of sentiment among online posts about six leading game console brands.

The posts analysed are those who have been cited by others and can therefore be regarded as recommendations (although not necessarily positive recommendations).

Figure 1 shows that Wii has the largest percentage of positive posts as well as the smallest percentage of negative posts (when combining negative and very negative posts). 20.3% of the posts mentioning Wii are positive whereas only 10.2% of the posts mentioning PS3 are either positive (9.6%) or very positive (0.6%).

Figure 2 (below) shows the same information but here each post is adjusted with the topical influence of writer. Example: A mention on the site Engadget.com counts one third more than a mention on cnn.com.

In figure 2 the difference in sentiment between Wii and PS3 is even more impressive. A full 28.5% of the influence (or impact) adjusted mentions of Wii are positive whereas the similar number for PS3 is only 4.9%.

The takeaway is, that of those who are cited (referenced by others) about Wii and PS3, Wii has by far the most positive proportion of mentions and among those with higher influence on the topic of “games consoles” the sentiment towards Wii is even more positive.

It is no surprise to me that Nintendo's profitability on Wii is greater than that of Sony's on PS3. Nintendo have a huge group of satisfied cusomers and influencers promoting their product for them.

What’s New in Online Marketing?

I am speaking at E-Consultancy’s event “What’s New in Online Marketing” next week (Wednesday 27th).

Let me know if you are going and want to meet up for a chat or to say hi.

I am really looking forward to what promises to be a very inspiring day!

I recently attended an industry get-together organised by Paul Birch and Robert Loch.

Here I met Nestoria’s Ed Freyfogle and we had an interesting chat about how vertical search and web mining are somewhat related. (See Ed’s blog for more detail).

For those of you who don’t know Nestoria I urge you to check it out. They are a fantastically well made vertical search engine focusing on real estate. A kind of better Google-for-real-estate.

Just like Sam Seti I can’t stop myself using it all the time to try and find the perfect place to live.

Clinton, McCain Leading Online Race

I was looking at some of the candidates in the US Presidential election through InfluenceMonitor.

John McCain has had a bit of a comeback while Barack Obama has slipped. Senator Clinton seems to be a clear leader in the Democratic field.

Figure 1 shows the 6 candidates’ relative share-of-voice of online media in the last 180 days. Notice how McCain and Clinton have an equal share of the coverage.

Figure 2 shows the 6 candidates’ relative share-of-impact for the same period. Here we can see that McCain’s share of impact is substantially bigger than Senator Clinton’s, reflecting the fact that although they had an almost equal amount of coverage, McCain’s coverage was mainly in more influential media.



When measuring share-of-impact the online voices are weighted according to their influence on the topic analysed. For example: When measured over the last year, NY Times has roughly 186% of the influence of the Washington Post when it comes to the debate on the US presidential election. When measuring share-of-impact a mention in NY Times will thus be counted with a relative weight of 1.86 over that of the Washington Post. Another way to look at it would be to say that a candidate would have to have coverage 19 times in the Washington Post to match the relative share-of-impact of a candidate getting coverage 10 times in the NY Times.

You can follow the graph in near real-time (4 hours delayed) on the Onalytica front page.

Unilever focuses on web research

Financial Times (p. 18 in print edition) carries an interesting story today about how Unilever is transferring their £272.2m annual budget for research online as fast as possible.

According to the article Unilever has found that web research is more accurate, faster and cheaper than conventional methods.

At Onalytica we are constantly doing our part to make sure online research becomes even more accurate, faster and cheaper.