How do you fight fake news? There are lots of options. But taking real news into Russia is rarely mentioned.
I’ve put here an updated blogpost that I originally wrote back in March 2014. It gives some simple ideas about how to use Facebook advertising against Putin.
The problem: Russia is full of fake news
It’s well known that the Russian government maintains political support by suppressing the independent media, and deliberately making political discussion online difficult. Russia is likely among the top countries in the world for people believing fake news.
So I wondered if there was a way to counter this, right in Putin’s backyard.
Using Facebook ads to fight Putin
In early March 2014 I started a small personal campaign to bring unbiased news to Russian speaking residents of Sevastopol, , the capital city of Crimea.
Finding unbiased news was simple. I found the Russian language pages of the BBC website and then set up Facebook advertising targeted at people who lived in Sevastopol.
Facebook advertising is quick to set up and reasonably cheap. Best of all it’s good at targeting people in specific locations.
Back then I thought it was a good time to extend this to Moscow (where Russian public opinion is split on the war) and to eastern Ukraine.
My ads reached 5,992 people in Sevastopol, resulting in 171 people clicking through to the BBC website – a fairly typical rate. In other words a reasonable number of Ukrainian or Russian residents. I paid an average of just under 10p per click – not unreasonable.
I hope that the impact might be magnified if people in Crimea then get into the habit of using unbiased news websites.
How to do this
Setting up Facebook advertising is easy – just follow this guide. Even if you’ve never done it before you’ll be able to set it up in 15 minutes .
If you want to get more ambitious there are alternatives for geo-targeted ads. Facebook is good because of its reach and ease to set up. YouTube also works well.
This gives you an idea of the sort of picture you should see:
And Kenya’s been developing mobile money for years, well ahead of European markets.
But western markets, especially Britain, are going in a different direction.
Relatively few people use GAF to pay for anything except the odd app on Android Play or the Apple Appstore.
It’s not like GAF aren’t trying. Every few months there’s a new attempt to get us to save our card payment details on our phones. Then we could easily pay by waving our phone.
For instance Apple have recently added made payment via Watch easier. Apple Pay integrations reportedly increase checkout conversion rates by 200%. And this sort of dramatic increase in conversions from Apple Pay has been reported in many comparable situations where people save their card details.
But there’s been plenty of evidence in recent months that most people aren’t converting to Apple Pay and its competitors.
I was intrigued by this. So I asked Transport for London (TfL) – who deal with millions of transactions annually covering £1.7bn. You’d expect that London as the leading city in the UK, itself one of the leading ecommerce markets globally, would be a major user of Apple Pay.
They show that only 1.5% of payments on the London underground system are by Apple & Android Pay. That compares to 17.7% by contactless cards. That’s 12 times more payments through cards than contactless. The balance in case you are wondering is people using London’s Oyster payment card – of whom 80% are topping up by bank card.
In other words people have the choice to use Android and Apple Pay, but they just don’t use it.
Figures from UK Finance, a trade body, show contactless payment using cards rocketing. 34% of card payments are now contactless, and use is increasing fast, up 130% in the last year. Britons turn out to find contactless payment even better than mobile payments.
Why isn’t Apple Pay taking off?
It seems to be the value of being first mover for contactless cards.
As Scott Thompson, Insights Director at Publicis Media says, “If you use a card (Oyster or credit/debit) and it doesn’t work, it looks like there is a problem with the card or the reader. Everyone has experienced it, so you get some degree of sympathy. But if you use a phone (or worse, a watch) and it doesn’t work, you just look like an idiot playing with technology that doesn’t work and getting in everyone’s way.”
I’m also told by industry experts that the RFID technology in contactless cards tends to work slightly faster and more reliably than the type of NFC used in phones.
So the key thing is practical. Contactless payment comes automatically with 111m cards being used in Britain. And there are 506,000 terminals that take payment. That means almost everyone can take one out of their wallet and pay.
You’ll virtually never wave your card at the bar of a pub for them to look at you confused. While if you wave your phone or your watch, they might look confused.
So while the barriers to people using Apple & Android Pay aren’t high, they are just high enough to slow their adoption. Probably not forever. But a good reminder that just because you might think that a technology should take off, it’s not the same as it going mainstream.
*Amazon is missing from this list because they do have large numbers of logged in users for their app. And, currently, they aren’t trying to be a facilitator of buying anything on any device. You still need to go through their website or app for everything.
We Are Social’s trends and statistics decks are a fast way to grab international comparisons. Look here for things like the number of people using Facebook in India versus Indonesia. As ever check you are comfortable with the sources before using.
Google Think is vastly ahead of their competitors in producing useful research. Unsurprisingly it’s largely based on substantive original data, often from the backend of Google products. Their Tools section is particularly useful with resources on data sources, emerging technologies and consumer insights.
Mary Meeker’s internet trends deck is read by most of the digital industry. It’s not quite as useful as it once was, but it is still unmissable. It is horribly ugly, and absurdly long, but always full of surprising insights and data.
Scott Galloway’s L2 consultancy has done a very successful job of producing league tables and case studies for everything from luxury handbags to soap powder. But he also does great analysis of how Google, Apple, Facebook and Amazon are changing our world. He sometimes overstates certainty of his conclusions, but it’s hard to argue with most of his big picture.
Karin has been my deputy twice now. More importantly she is great on social data – for instance uncovering big holes in Twitter’s gender data. She has also been a leading light in Democrat’s Abroad for over 10 years so is excellent on political messaging, US politics generally and grassroots campaigning.
Richard tweets on behaviour change and marketing. His simple twist on most Twitter is to screengrab books he’s read. A small thing but it provides a bit more depth than a typical Twitter feed. His guest editing of the APG blog is a superb reading list on behaviour change.
Digiday constantly provides a good stream of interesting and useful news.
*This excludes most of my political reading which is not really relevant to most readers of this blog. On politics I highly recommend market researchers like James Morris, Marcus Roberts, Ian Warren. And John Oliver and Trevor Noah do superb work making complex policy simple.
Among Android users 9 of the top 10 apps are from Google or Facebook. On any measure – from users, to time spent – Facebook and Google are far ahead of competitors.
While Facebook has the social networking giants (Facebook, WhatsApp, Instagram and Messenger), Google has a wider variety of services, from YouTube and Search to Maps, Gmail, Drive and Chrome. Even Blogger, often forgotten, has almost as many users (9.6m) as Snapchat (10.3m).
This dominance can be seen everywhere.
Facebook has three of the five biggest apps
Now that WhatsApp has overtaken Twitter, Facebook has three of the top five apps.
Audience reach of top social networks (UK adults)
These apps notch up astonishing levels of use. 94% of Facebook users have used it in the last week, and on average users check it 12 times a day. WhatsApp is checked 10 times a day.
YouTube increasingly looks like TV
YouTube had 42m users in 2017 – far ahead of any other video sharing site. Increasingly YouTube is taking time from traditional TV viewing, with younger views spending over an hour a day watching it in March 2017.
SMS is suffering from instant messaging
Instant messaging is killing SMS, which is down 35% since 2011.
While there’s no sign of email falling significantly this year, it’s no longer as dominant as it was.
Snapchat has gained over 3m new users this year but is still mainly restricted to younger users. Even in its home territory of messaging, Snapchat is a distant third, with 10m users to Facebook Messenger’s 22m and WhatsApp’s 18.2m.
Twitter isn’t dead
Twitter has gained almost a million users in the last year. While the company struggles, it continues to be a significant second-rank player, alongside properties such as Pinterest, Snapchat and LinkedIn.
Talking of which, LinkedIn appears to be in some trouble, losing 4m users this year. Given recent improvements in the app, this is one of the biggest surprises in the report.
The ‘also ran’ social networks (Unique audience, millions)
Two trends underlie the Ofcom report…
Driving this year’s figures is the continued growth in older internet users and the increasing dominance of smartphones.
Older users continue to grow fast
Most older people are now online and this figure continues to grow. 53% of over 75s are now online, as well as 78% of 65-74s.
This group, as they get more experienced, are using a wider variety of services, for more time, every day.
For instance 69% of over 54s are now using social networking, and almost half of them – 46% – are using Facebook.
54% of over 54 year olds are using WhatsApp, doubtless because of its similarity to familiar SMS services. As Facebook starts to monetise the app, there’s a huge opportunity to reach this age group via WhatsApp.
Older internet users are also increasingly users of YouTube – though currently still watch only 6 hours per month. If they start to get the YouTube habits of younger viewers, then the TV watching landscape will transform.
Smartphones are now owned by 76% of people
Ownership is up 5% on the year, so smartphones are now clearly the most common way to access the internet – well ahead of laptops and tablets. Meanwhile desktops continue their slow decline, with only 11% of people considering desktops to be their most important device for internet access.
And finally the dog that didn’t bark…
The internet giants have been trying to crack mobile payment for years. While mobile payment is commonplace in China, it’s still not mainstream in the UK. Apple Pay, Android Pay and Facebook have all tried. This year it seems they’ve failed again. Only 5% of people have tried mobile payment, up 1% on the year. As to why, it seems likely that using your contactless card is simply easier, with cards now used for 30% of payments.
Most of my election effort will be trying to elect Lib Dems. But if you are non-party political and want to influence the election, this post is for you*.
Recognise that seats matter more than votes
In the UK political system seats are all that matter in practice. You probably can’t remember what percentage of the vote Labour got in 2005. But you can almost certainly remember who was in power after the 2005 election.
So anything you want to achieve needs to influence how many MPs get elected who agree with you.
Not all seats matter the same in the election
Britain’s electoral system means that most seats stay with the same party time after time.
Roughly 200 seats, out of 650, really matter.
Not all votes are the same
Point 2 means that the only votes that really matter are in the marginal 200 seats.
But roughly 50% of voters always stick with the same party. Leaving only 50% of people worth trying to influence, in the 200 constituencies you are targeting.
Not everyone votes
Voting is voluntary in Britain.
Even in a really high turnout election, only about 70% of people will vote.
So you need to target a specific type of person
Add together points 1, 2, 3 and 4 and it means that you need to target swing voters in swing seats who might realistically vote.
Who are these people?
They are a varied bunch. But we can look at what is most typical of them.
Almost every bit of research I’ve seen says that this group is concentrated:
Living in the suburbs of Britain’s cities and towns. This is where the swing constituencies are. Think of suburban Leamington Spa or Derby.
Middle aged. Young voters tend to have very low turnout (and there aren’t enough of them). Old voters tend not to change their minds, after a lifetime of voting a particular way.
Not very interested in politics. In fact giving very little attention to politics day to day. This group typically make up their minds during the election campaign, often on election day. A surprisingly large number make up their minds in the voting booth.
If you want to make an impact consider if you are going be relevant to this group of voters.
If not what are you going to change?
* Psephologists will notice some significant simplifications here. For everyone else – if you seriously doubt any of these points, drop me a line and I’ll dig out sourcing.
Election 2017 will be a test of both messages and digital campaigning for Britain’s political parties.
The big battle in the campaign will be to frame the election choice. There are two possible frames.
Frame 1: Leadership
In this frame public debate focuses on who would be best Prime Minister. This is probably the campaign Theresa May wants.
Theresa May will do well in this scenario. The public know her, and, largely, trust her. Jeremy Corbyn will do disastrously. Many members of the public don’t have a fixed opinion about Jeremy Corbyn. This will change after 7 weeks of Jeremy Corbyn being constantly linked to terrorism. Labour could do extremely badly.
I’m biased, but in this scenario Tim Farron has the opportunity to break through as a new voice. Tim is a clear communicator and funny. From an normal background in the north of England he’s as far as you can be from a typical member of the political class. However he’ll face the challenge of being seen as a credible Prime Minister, leading a party with just 9 MPs.
Frame 2: Brexit
In this frame the public focuses on Brexit for the length of the campaign.
Theresa May will face an opportunity to pick up a lot of pro-Brexit votes from Labour and UKIP. But she’ll also face two risks.
Firstly the Brexit focus might help UKIP. Secondly moderate Conservatives may defect to the Lib Dems in England, and the nationalists in Scotland and Wales.
Again Labour look set to do extremely badly in this scenario – losing a large proportion of their votes to either Lib Dems or Labour or nationalists.
Again I’m biased, but there’s a big Lib Dem opportunity here.
The digital election
A simple way to think about the impact of digital on the election is to consider reach and impact.
The Conservatives will have a significant advantage. They will be able to buy huge reach on Facebook and YouTube, as they did in the 2015 General Election.
Labour have a secret weapon though. Back in 2015 they had around 6 million email addresses on their database. And, whatever you think of Jeremy Corbyn, he gets a lot of free reach on social media. While they have been relatively uninventive with their email, they have a significant, free, reach to the public. And you can assume they will raise several million pounds this way.
However reading accounts of the 2015 Conservative and Labour campaigns, the Brexit campaigns and Trump’s election here are three areas to watch:
Impact on marginal constituencies: How much advertising is seen by voters in marginal constituencies? This should be reasonably easy to test through polling, as Lord Ashcroft did, crudely, in the run up to May 2015.
People often forget about Facebook Groups. They’re low profile, and fairly simple. But they have over 1 billion users. Anecdotally it seems they are influential over everything from private business discussions to the hottest parties in Los Angeles.
This makes Bots for Facebook groups interesting. It will be possible to engage in a Group without being allowed in. For instance BT Sport might create a Bot with sports results for private football groups. Or a software company might create a news bot for a specialist set of customers.
On that note, it turns out the most effective ad of the Trump campaign used an old video of Michelle Obama attacking Hillary Clinton. It’s routine for political campaigns to follow their opponents everywhere, hoping to catch them off-guard. I wonder how many corporates have considered this?
There are really two ways to fix a problem like this.
Option 1: Whitelist appropriate YouTube channels
The first way is to whitelist YouTube channels that advertising appears against. For instance you get the most popular 100,000 YouTube channels and put them through a verification process that weeds out inappropriate content. Human tagging, combined with machine learning (in the literal sense), would make this expensive but not impossible.
However the, say, 1.9m channels which would not get verified are 95% of the channels, but likely only, say, 20% of the views. So YouTube would need to give up that ad inventory. Or it could sell it to less squeamish advertisers at a lower rate.
Option 2: Find inappropriate YouTube videos
The second option is messier but less costly for YouTube. It relies on the fact that people who put up ISIS videos want them to be seen. So YouTube can put human review in for any video that:
Isn’t from a known safe channel or user.
Has any tag or keyword that is risky (e.g. ‘Iraq’).
Has more than, say, 400 views (And so is likely to have any meaningful impact)
Is gaining views quickly.
Add these together and the number of videos to review drops dramatically. Get your reviewing mechanism to learn from human judgement, and you should, fairly quickly, be able to handle the problem.
YouTube/Google have some of the world’s best machine learning experts, huge budgets and good reasons to move quickly. They can fix this.
Technology companies constantly hype their own processes and products. Often this hype is technically truthful, but misleading. But hype takes on a life of its own, misunderstood or exaggerated. Eventually hype leads to absurd claims. These cause real damage.
To protect yourself look at three laws of marketing hype.
Law one: Impossibility – The technology doesn’t exist or is impractical
Impossible claims are at the centre of technology hype. Or the hype focuses on things that might be technically possible, but impractical.
Mass scraping of data is usually impossible
First consider a Guardian claim about Cambridge Analytica’s work for Donald Trump during the 2016 election.
The article claims that Cambridge Analytica harvested data from people’s Facebook profiles.
Here’s the problem though: This is almost impossible. The vast majority of people’s Facebook data is private. This data can only be seen by their friends or if they choose to reveal it to a company.
Of course you could try and scam your way to people’s data. You could create thousands of fake Facebook profiles. Then try to befriend all 128m American voters. Then copy their data. While this is possible on a small scale, Facebook is generally good at weeding out large scale scams like this.
[Update: The March 2018 revelations about Cambridge Analytica revealed that they did managed to get 270,000 people to use an app that harvested around 50m people’s Facebook data. This has been made impossible since April 2015 due to an API change. So while mass scraping of data is now hard – and was in the run up to the 2016 election – it was possible previously. Note that the decay rate of data quality will make a big difference to whether this data was useful in 2016]
No, Facebook doesn’t know more about you than your partner
A related example is almost any article that claims that companies know huge amounts about you. Yes, there is a lot of data, but it’s not always meaningful.
To test this visit Amazon. Then ask yourself how good their recommendations are. They’re probably ok – but not amazing. Amazon have more data to make recommendations about what to buy than virtually anyone else. Yet they struggle to get it right. To complete your personal test visit Google, Facebook and Apple’s websites. Have a look at how well personalised they are.
Why is this?
The vast majority of data is either private, anonymised or just not very useful. If you want a guide to what’s possible then have a look at the world’s best companies at selling data. Simply create an advertising account on Google. Or look at the business sections of Facebook, Amazon, Experian and Axciom.
Impracticality is closely linked to impossibility.
AI is currently going through a bubble that is often based on impracticality. Read reports on autonomous cars and you’d think every taxi driver in the world was about to lose their job. Then look at Uber’s current testing, which recently leaked, and you’ll find that humans had to take over the driving every 0.8 miles on average. That’s a long way from a technology that is going to satisfy regulators and insurance companies.
Illegal is also impossible
A final angle on impossibility is the law. Is the technology legal? And does it comply with relevant social network policies? Data protection laws, and discrimination laws, might simply make it illegal. And if a company scrapes millions of people’s data from Facebook they can expect to be sued.
Law two: Value – New technology isn’t worth the effort
New technology might be practical and legal. But it often isn’t worth the effort compared to easier and cheaper approaches.
There are lots of simple ways to improve digital campaigns, because they are simple to test. It’s common for testing to increase the effectiveness of a campaign by 10-20%, quickly and at low cost. So the second law is that technology may not be a better use of your time than simpler alternatives.
Another way to look at this law is to ask if you have exhausted your current testing programme. Have you got the right strategic choices? Are you using the right channels, for the right purposes? Have you optimised your customer journey, from acquisition to conversion? Is your creative optimised?
Even tech companies don’t always use cutting edge technologies
I recently reviewed the digital marketing programmes of five of the world’s leading marketing automation providers. If anyone is going to be using cutting edge technology, it’s this group. Yet all of them fail on at least one basic measure. Several have very poor quality email programmes, with virtually no personalisation. Some of them don’t re-market to people who visit their website. Their websites are generic even when they know something about you.
Why is this? Some of it is inertia. But it also reflects a judgement that new technology isn’t worth the effort of implementing it.
Apply the second law to claims that people can predict the future (e.g. the X-Factor). You could try through social listening but that’s hard to get right. It’s easier, and probably cheaper, to commission a traditional poll.
Law three: Reach – Technology doesn’t reach enough people to work
A valuable technology has to reach, and influence, enough people to justify its cost. Reach comes down to two things:
Penetration – What proportion of the target audience encounter your technology?
Time use – How long do your audience spend with the technology?
The problem with anything new is that not many people use it. By definition. So there needs to be a route for it to penetrate its market.
This can sometimes happen organically. But most of the time this needs time and marketing.
Apply the third law to VR discussion and something becomes clear. Most VR won’t get to enough people to make a difference. Why? Because there’s no distribution system for it, unless it’s through Google, Apple, Facebook or Amazon.
What is the most hyped technology?
Look at the three laws and what areas of technology look overhyped currently?
Not enough reach, and not much evidence of impact in many cases.
AI that’s implied to be fully automated. If you re-cast these claims as ‘software tools making people smarter’ then there are plenty of sensible cases. But implying that you have an artificial intelligence, when you just have programmatic media buying, you’re pulling a con.
Almost all discussions of Social media that don’t mention reach.
‘Data science’ that claims to know people better than they know themselves.
 There’s also a claim that Cambridge Analytica used ‘machine learning to “spread” through their networks’. This is a confused claim, that might charitably be read to mean that Cambridge Analytica used machine learning to understand what content was most liable to be shared on social media.