Friday, May 17. 2013
Implicit relationships people seek from products (source: Simon White, Draftcb)
Last week I attended another event i think was very useful seminal in pushing Social Media forward, the ChinwagPsych event, which reviewed the emerging lessons from the emerging fields of digital psychology and anthropology. It was really good as well because the amount signal was high, and the amount of noise from snake oil, bullshit and hype was low. Here are some notes of mine from the event.
Nathalie Nahan, who wrote Webs of Influence, on Website design in the Social era.
- Trussst is what stops people buying online, as customer service/delicvery etc is unclear. Consumer reviews are good at creating trust, also earned media. Using recognised logos eg paypal also helps
Leigh Caldwell, Inon - Psychology of Pricing
- This is an emerging new field - cognitive economics
Simon White, Draft Cb - Why are people NOT using all this stuff?
- Old models (persuasion) only lead to accidental success as 95% of decisions are instinctive, not rational/ logical
The new thing I got from Simon's talk was this:
- People buy things to achieve goals, they do not have a "relationship" with brands as such. And their real goals are the implicit goals, eg buy Mercedes to feel powerful
Simon Hill, Wazoku - Open Innovation - A rereshingly free-from-hype talk about the reality of Open Innovation.
- technology is not the issue in Innovation
I then had to go to a client meeting, so missed a few talks and lunch (boo), returning in time to catch:
Steven Haggard & David Stillwell, Cambridge Predictive
I first heard about them awhile ago when they started to put together patterns of connected likes, on Facebook, they mentioned some typical insights e.g. people who like Terry Pratchett and computing tend to be introverted and Likes on Facebook can tell relationship status (I'll bet!!). They started to look at Business Applications, for CRM, trying to find predictive qualities of personality for honing the Marketing message; keywords, behaviour types etc. They mentioned as an example the Relentless fizzy "energy" drink going up against Red Bull etc:
- Its roots were in music roots so they started look at interconnections there
Cat Jones, Unruly Media - Viral Video Chart
- built Unruly Sharerank algorithm by testing large no of hypotheses of what drives sharing vs actual sharing
Milward Brown (Similar findings to Simon White, above)
- The only people who were shocked by behavioural economics were economists (rational man)
What was new is they have tested a number of these new approaches against Ads
- Most useful method they have found is facial response, map facial
The next 2 talks were about Smart work, and were interesting in that they seem to apply a "psych" layer to the Quantified Self movement
Design by Day (Book on smart work) Nokia/Anthony Mayfield
- using mobile technology to improve productivity
Prof Karen Pine - "Do something different"
- Use technology to remind you to do something different that is good for you, force behavioural flexibility
Benjamin Ellis, Social Optic
- how to use technology to change larger groups - uses social data to drive changes in organisations
Daniel Bennett & Marina Clement, Ogilvy Change: Case study - the missing £2
- Rory Sutherland started behavioural economic arm, heavy usage of outside academics. Case study was that people are stopping buying newspapers, so how do we sell them again. Approaches were
Those 4 "nudges" hit 257% ROI, I asked which ones had the most impact, they said they didn't know. I find that hard to believe
Fascinating and worrying in equal measures.....
Thursday, May 9. 2013
Broadsight Simplified Value Creation Flowchart
We have been asked to be on the Microsoft Business Re-Imagined panel on the 15th of May, looking at the potential impact of Social Media in business. We've been consulting to and building social media systems for clients since 2005, and it seemed like this was a good time to boil down our experience down. Above is a simple value creation flowchart, and we look at how, in our experience, social media can impact value creation. Stripped to it's bare bones, a business creates sustainable value by increasing revenues and/or reducing costs. Social Media is a new set of technologies that can help in a number of ways.
Essentially, there are only 2 ways of increasing revenue, which is sell more stuff, or increase the price at current volumes. In my view, Social Media is more powerful (with current technology, anyway) in dealing with Consumer sales, rather than Business sales, as the main cost in a consumer sale is reaching the large mass of disparate consumers. With business sales the target market is much easier to identify, and there are less customers to contact so current approaches work well.
Sell More - Social Media is a potentially very powerful tool to generate new demand - to find new customers, to bring them to the enterprise, create trust, ease their purchasing journey, and help optimise website design to maximise sales throughput. Taking it to greater extremes, Social Media data can be used to start to psychologically profile your customer base to understand what sort of people may also be your customers. It is also a very powerful tool to optimise the product - to discover the features or configurations that customers really value, and you can identify what competitors do well and include those in your product. But it is not a substitute for existing methods today, it is an adjunct, it can't be the only tool. It is not an appropriate tool for overt "hard sell" marketing, for example.
Increase ARPU (Average Revenue Per Unit) - Social Media has two main functions here - to aid in communicating the value proposition of the product, and to improve the perceived value vs competitive offerings. Communicating the value is fairly straightforward, as it serves as an extension of traditional channels, with the added benefit is that it has a strong feedback loop so it is quickly possible to see what is working and what is not. It is also probably better at communicating implicit values than more traditional media. Social Media can also help to improve the pricing point by optimising product differentiation amomg dofferent customer groups, and find pricing points for these different customer groups. That feedback loop, and the data it drives, can be used to to find attractive product combinations, and to optimise the website design to maximise value per sale. Taking it to greater extremes, Social Media data can be used to start to psychologically profile your customer base to understand their hot buttons better
Again, essentially there are only 2 ways to reduce costs - reduce operating expenses (Opex) and reduce Churn (Customer defection). I will ignore Capital expenditure (Capex) for now. Social Media in my view is as useful in both consumer and business facing enterprises, as it's power is about increasing productivity and effectiveness in reducing costs
Reducing Opex - In most companies, there are two major cost areas - raw materials and labour, the sum of them is typically the "80/20" of the cost pie (companies with near zero raw material costs tend to be professional service businesess, with very high labour costs). So far in or experience the two major Social media impacts are from:
(i) getting better market information (both pre and after sales) from customer to company, allowing the company to both reduce costs or lead times of raw material while not reducing value, and being able to better place its human resources where it really matters - it can work like a real time value engineering approach. It's not just useful for line operations, social media can be used to influence better design and innovation, and can be used to increase "brain cycle cpacity" by tapping into customers and the overall milieu without having to employ it
(ii) getting a better flow of information between people in the company, so co-ordination is better (less balls are dropped because A didn't know what B knew about customer X) and spped of reaction is faster.
The third cost element, overheads, is interesting. I have some thoughts about using Social Media transaction data to better allocate some overheads, but I don't have a fully formed set of ideas and I haven't seen it put into practice anywhere yet.
Reducing Churn/Increasing Retention
Churn is often not well understood, as many businesses are not aware of the huge differences in cost between retaining an existing customer, and finding a new one. There is often an order of magnitude difference. Thus reducing churn can have a massive impact in cost reduction and revenue increase Social Media can be used to aid customer service, to serve as an early warning for customer problems, to find out what people really value in post sales service, and to improve the product lifecycle. Social media also means bad service is more likely to leave a company's reputation punished, which can also impact sales, as customers typically research online before buying. In saturated industries, having a better churn than the competition can radically alter the market share and strategic positions within a few business cycles.
A brief word on Capex costs - if Social media is helping a busines to make better use of existing assets, in theory it will slow down future Capex requirements - but Social Media technologies do have Opex and Capex costs of their own, and these are typically incurred early up, while the benefits are then gained over a series of cycles. Which brings us to the dreaded Return on Investment (RoI) question.
Return on Investment
For any new technology, ROI is hard to work out, as few case studies exist to allow calibration of cost and benefit. If history is any guide, new and risky ideas are typically implemented first where forces are greater than a pure ROI worry:
- Piloting: trying out the New new thing in some areas of the business, somethimes structurally, often though by "Intrapreneurs" who do it locally out of passion, or seeking promotion etc.
But eventually, for Social Media to take off and scale, believable ROI needs to exist. We are dubious of some of the various "Returns on" currently touted for Social Media, as it is hard to tell which are valid proxies for hard to measure benefits, and which are just Snake Oil. Our test is that if a proxy measure cannot be linked to an underpinning economic benefit logically, its more likely than not to be snake oil.
So far we have seen 3 meta-impacts of Social Media occurring
Firstly, there is a synergy when multiple of the above areas are pursued. The marketing listening systems can influence the customer satisfaction and product design systems, the customer satisfaction system can improve the marketing message, better staff co-ordination can improve customer service and salesforce knowledge and thus effectiveness. In general as more information flows in a business, better decisions are made throughout the business. But its not a given - if organisation culture is not open, if individual reward structures do not encourage sharing, if management use the new dataflows to further expolit staff, these systems can go nowhere, even potentially accelerate problems as they are just better ways of making sure all the sh*t hits the fan.
Secondly, the same influencing ability that works on attracting potential customers can influence sentiment, and thus share price. But this has always been a temporary game in the past, and its unlikley Social media will be any better at selling the sizzle if there is ultimately no beef.
Thirdly, expanding on this, a basket case will be exposed far more quickly - disaffercted customers, employees, investors etc will make their feelings known. In teh old days, they sued to say one disgruntled customer would on average tell 7 people. Now they will tell tens, hundreds, thousands, will write on review sites, will push negative pages higher in the search rankings than "official" company narraticves, etc etc.
Beware the Snake Oil
There are too many Social Media snake oil merchants promising miraculous cures today. We talk about what Social Media can do above. This is what it cannot do:
If we had to give our sanguine view, Social Media is the sort of cluster of technologies that today can give low % increases to all those areas we cover above - but once you sum up say a 5% increase in sales volume, a 5% increase in ARPU, a 5% reduction in OPEX and 5% reduction in churn, you wind up with a shift from (ay) 5% margin to near 30% margin. That is life changing for any business, but it has to be done within the current business systems to get the full impact. The medium may be the message, but it isn't the modus operandi*.
The Downside Risks
As with any powerful new technology, used improperly it can blow up in ones face. There are two main dangers that have emerged so far
The devil in doing all of this is of course in the details. So, we hope to see you on the 15th.....
(*With the exception of wholly new businesses that are Social Media businesses, of course - but that is the subject of another post)
Tuesday, April 23. 2013
After all this hullabaloo today, all you need to do is look at Apple over 35 years and you will see that they:
Its a waveform. Find a wave, ride a wave, find the next wave. Quarterly numbers are irrelevant. They rode the PC wave very well, then the portable music device, then the smartphone, now the tablet.
What will they go after next? And will they be able to reproduce Job's genius for getting onto the board at the right time?
Update - my colleague Keith McMahon nailed the current tactic perfectly when he notes that market expectations currently outstrip reality, hence best strategy - buyback shares
Sunday, April 21. 2013
Broadsight Hierarchy of Internet Needs (after Maslow)
This week, I was allowed out of the office for a trip to the Spring Lecture day organized by the Society of Cable Telephony Engineers (SCTE.) It was an eclectic mix of lectures, although I found a theme emerging about the economics of bandwidth. If you are interested in the details of these lecture (and some on other topics), you can see video of the lectures at http://tv.theiet.org (and search for “The Society for Broadband Professionals”)
Several of the lectures were on the use of new technology to extend the life of existing plant.
Mourad Veeneman, from Liberty Global, spoke about the upgrades to the DOCSIS standard with the 3.1 revision and the focus on getting higher data rates over cable to compete with the emerging technology of fibre to the home (FTTH.) Like many upgrades to transmission (line coding) standards, DOCSIS 3.1 seeks to take advantage of advances in modulation and error correction theories supported by extra processing power at both ends. Also to make use of more spectrum on the cable.
Stephen Cooke of Genesis Technical Systems, spoke about a new architecture to enable rural broadband by sharing the pairs in the bundle from the exchange (Telco Office) to the local distribution points (pedestals for North American viewers.) By sharing the data bandwidth on the exchange back haul, what little bandwidth might be available on a long line can be used more effectively by pooling at the distribution point and creating a resilient ring around the community being severed. This doesn’t rely on a leap in coding technology, but the insight that Internet connectivity is always contended, so in this case we might as well move the contention out to the edge of the network. A cable drop might have in the order of 20 to 30 pairs and at the end of a long line, those pairs might support 500k each, but bundled together that’s still a respectable speed. The Genesis system also allows regeneration at intermediate points, so will usually do a lot getter that that figure suggests.
We also had a lecture on the use efficient development and operation of fibre in the network core. For me, these lectures illustrate the point that bandwidth must be provided in a way that is economic (and practical) to customers and makes a profit for operators. There is often a temptation to start a project with the idea that we should “do this right” and not be held back by “legacy.” However, engineering (in my view) should always be “the art of the possible” or perhaps “the art of the profitable.” This means we need to find clever fixes to maximise current plant, equipment and organisations. DSL has been a brilliant way of leveraging copper pairs that were designed for 3KHz voice and extending their life. DOCSIS has done a similar thing for cable networks, many of which were laid before the Internet had even routed a packet.
By the way, this principle can also be applied to software. It's tempting to start again "with a clean slate", but it can be dangerous to underestimate the value of old software that has matured under years of trial, error (and hopefully, fixing!) A nice illustration of this is the the adoption of DOCSIS Provisioning of Ethernet PON (DPoE) by the EPON FTTH standard. This allows ISPs to use their old cable billing and OSS systems by connecting to a DPoE API that presents a "virtual cable modem." This was discussed in the talk by Jim Farmer from Aurora Networks.
So it’s clear that bandwidth is valuable and has to be provided economically. However, creating and capturing value are not the same thing and a couple of points illustrate this.
The first point regarding the growing conflict between 4G Mobile services (LTE in the jargon) and existing TV services was discussed by Dipl. Ing. Carsten Engelke from ANGA. Both terrestrial TV and cable services run in bands that go up to the 700 and 800MHz range. This applies to digital and analogue TV (for those countries that still have analogue.) The mobile industry has persuaded governments (thought the ITU World Radio Conference process) to clear the 800MHz band and soon, the 700MHz band for extra 4G data bandwidth. This means that terrestrial TV has to move, which imposes costs on the broadcasters without benefits. To be fair, they have a privileged position in the first place and can do with less bandwidth once they turn off analogue. A bigger problem is for the cable industry, where their business model is essentially to compete with DSL and FTTH. This means that they are relying on most or all of the bandwidth in their cables. Although it’s early days for LTE in the 800MHz band, there are examples of the LTE signal getting into the cable and blocking TV. Although it’s a signal from the mobile tower, it becomes a problem for the cable company. If the signal is leaking in through a customer's TV (due to unintended pick-up) there may not be much they can do about. So the mobile company has captured some value to the cost of the cable company. I am not making judgements about companies here as they are just using the bandwidth that has been licensed to them. However, it is worth making the point that externalities become complex and may become more so with increasing use of power line and cognitive radio.
The other example is allocation of Wi-Fi frequencies, which have been a huge benefit to businesses and consumers, but risk becoming a neglected spectrum user. Wi-Fi has two main bands allocated to it. Most common in the 2.5G range and another in the 5G range. (5G is getting to the point where radio is starting to behave like infra-red and doesn’t like to go through walls, so is less useful than 2.5G.) With only 3 non-overlapping channels in the 2.5G range, Wi-Fi is oversubscribed in most medium and high-density residential areas. It wouldn’t be hard to add another band to mitigate this problem and would, arguably, be a significant benefit to users. However, no one appears to be pushing for this at the WRC and so it’s unlikely to happen. We could speculate that this is because residential Wi-Fi is not directly billable and so no one can capture the value and therefore have an interest in promoting it.
To sum up - as bandwidth provision increases, we keep finding ways to use it, from GIFs to music/speech to video and now HD/4K video. I am sure we will carry on filling up the pipes, so thanks to the engineers who keep re-building them. This brings to mind a review I read (a long time ago) about the first 9600bit/s modem, which went something like “this is all very well, but no one can type that fast – so what’s the point?”
Friday, April 19. 2013
There was a very interesting article in the Grauniad the other day, arguing that News can be toxic (the irony of the article being in a newspaper is there...). Its based on an essay by German writer Rolf Dobelli and argues that News deliberately plays to some of our more primitive instincts, so a glut can be bad for our health. In summary, the argument is:
News misleads. . It often looks at the wrong problem, or over-eggs the spectacular. We are not rational enough to be exposed to the press. Watching an airplane crash on television is going to change your attitude toward that risk, regardless of its real probability. If you think you can compensate with the strength of your own inner contemplation, you are wrong. Bankers and economists – who have powerful incentives to compensate for news-borne hazards – have shown that they cannot. The only solution: cut yourself off from news consumption entirely.
The author says he "has now gone without news for four years, so I can see, feel and report the effects of this freedom first-hand: less disruption, less anxiety, deeper thinking, more time, more insights. It's not easy, but it's worth it.". I must say I did the same, a similar time ago, after spending an extended period outside the UK and realising missing out on the daily News had a similar effect. I prefer to read "the News" once a week from journals eg the Economist, as very little that happens on a day to day basis is much more than mental chewing gum.
So here's the kicker for this article. What I have been using, a lot, over the last few years is social media of many forms. I am increasingly coming to the conclusion that the more immediate types (like Twitter etc) have a similar effect to News if over-consumed and have started to curtail my usage of it too (except for blogs, which I see as the more investigative element). If you replace the word "News" with "Social Media" in the above passage, it is largely still true in my view.
Wednesday, April 17. 2013
Source: FRS blog, Princeton
Picked up from the New Scientist:
Sociologists have long known that people have fewer friends than their friends do, on average. This strange conclusion, known as the friendship paradox, arises because of sampling bias: people with a larger number of friends are more likely to be your friend, so they get counted more often.
Re the Friendhsip Paradox, it is also seen on Facebook - NYT
You spend your time tweeting, friending, liking, poking, and in the few minutes left, cultivating friends in the flesh. Yet sadly, despite all your efforts, you probably have fewer friends than most of your friends have. But don’t despair — the same is true for almost all of us. Our friends are typically more popular than we are.
In fact its a power law thing, in any network the "connectors" at the centre of friendship nets have a large number of friends, the less connected on the ouskirts have far fewer, so the "average" is higher than the average peripheral user owing to the high score of the connected Ones - see picture above. (Read the maths in the article, its a very good primer on social graph link weightings). The other highly connected strategy is to be a Social Butterfly, a being peripherally connected to many friendship nets
In short, unless you are the social hub of your friendship network, or a social butterfly, you will suffer from the Friendship Paradox - its one of the Power Laws of Nature.
Thursday, April 11. 2013
At the top of the South Sea Bubble of 1711-1720, investors were eagerly pouring money into an enterprise advertised as:
"a company for carrying out an undertaking of great advantage, but nobody to know what it is"
At the (current) top of the Bitcoin Bubble (2011 - ?) investors are pouring money into:
"a company* for carrying out an undertaking of great advantage, with a currency that doesn't exist, generated by a method that nobody is to know what it is (and wouldn't understand if they did)"
This time, of course, It Will Be Different.....
Or alternatively, read George Santayana
* I use the term loosely
Wednesday, April 10. 2013
Bitcoin crashed today, spectacularly (see 3rd diagram below). To protect your wealth there are 3 things you need to know, all fairly well documented from other bubbles:
1. It crashed before, the last time there was a major frenzy, and it took years to recover. In 2011 to be precise, we wrote about it then, here was the graph at the time:
2. Bitcoin is a speculator's toy, and the fact it rose so fast (from c $15 in January 2013 - approximately its crash price in 2011 - to more than $215 in April) is a burst waiting to happen, and ordinary people have been buying it in droves over the last few weeks (and twittering about it - that is the equivalent of cabbies giving you stock tips) means that We Are Here
In fact, if you want to see that in actual crash-o-colour this is it
Bitcoin price rise - and rapid fall - since January 2013
3. the last thing you should know - its a Virtual Currency fercrissake, it doesn't exist! You don't even have to go to the trouble of printing real paper phoney money if you want more, you just flip a switch and make more. OK, I'm simplifying, but you get my drift - In this Digital Age I think we need to invent Broadstuff's Law - Don't speculate on assets which cost ~ $0 to produce more of.
(Update - I have been rightly pulled up in the comments, what I meant by "produce more of" is the marginal cost of generating another bitcoin/virtual currency of your choice, once you are set up to mint them)
I know, I know - you can't make more Bitcoins, we are told. The software is safe, its based on the principles of cryptography*. Wanna bet? If you go back to March 2013...(Wikipedia)
"The fork of March 2013
We have been here before, people.....
We warned ya with Second life in 2006, we warned ya with Bitcoin in 2011, and we will warn ya again, and again. You're better off investing in Tulips or South Sea property.
*As it happens, we have more than a passing knowledge of cryptography, and its worth knowing its seldom the algorithms that are corrupted, but the men-in-the middle in the chain often can be.
Tuesday, April 9. 2013
Unscientific, amusing - and surprisingly accurate - Sentiment Chart on Margaret Thatcher's death by Martin Belam
For those who may have missed it, Margaret Thatcher, British Prime Minister in the 70's/80's, died yesterday. She was, according to the commentariat consensus, "extremely divisive". "Extremely" doesn't factor in our more precise world of Big Data Analysis (we used to call it data analysis, but what with inflation - you know how it is these days), so we decided to see just how much, and set our trusty old media analysis engine onto Twitter for a spell of Big Data bump n' grind (the term Thatcher is still ticking over on Twitter faster than a petrol pump eats pound notes by the way).
Anyway, much Big Chugging later and we can say safely that Twitter is about 44% against and 39% for Margaret Thatcher, ie the ratio of For : Against is about 1.13:1. The error on sentiment analysis is typically 10 - 15% so its near as dammit a wash in terms of divisiveness between the Maggie haterz and fanz (The Twitter demographic is still more left leaning than the national average, so I'm not that surprised it swings slightly to the left, as it were). An Ipsos/Mori poll shows that she is still the most popular post war British Prime Minister by some way, but she was seen as the most capable (39%) far more than liked (22%). For comparison, runner up Tony Blair was also "liked" at about 26% but seen as only 27% capable. The rest make for pretty sorry reading.
What is more interesting though is what is meant by "extreme" - to have a total of 39%+44% = 87% taking a position is a very high %, usually reserved for spats about various 'isms and causes du jour on Twitter, and even then many people tend to play the more even handed (or popcorn eating sports fan on the bleachers) role. For comparison the average Social business would be delighted if more than about 20% of their twitterstreams got really passionate one way or the other (a national broadband outage would possibly do it), and the parallel-running Twitter'Meedja discussion* about MumsNet got to about half that at its peak.
As to actual topics of - ahem - "conversation" in the Thatcherstream, the graphic above by Martin Belam (@Martin Belam), though data-poor compared to our big data crunth-a-thon, and far more tongue in cheek, actually captures the zeitgeist of the online discussion* very well.
In vitriol veritas, as they say.....
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