Why Do Some Ideas Go Viral?

What is the Bandwagon Effect?

For an idea to go viral people have to copy and share it with other people they interact with.  But what makes this process continue to build up momentum for an idea to spread throughout our social networks? Many marketers focus on targeting “influencers” but is this the right approach? Analysis of the bandwagon effect may give us some answers to these questions.

The bandwagon effect is a psychological tendency where the adoption of ideas, products or behaviour increases with the uptake (or perceived uptake) by others. This means that the propensity to take-up something rises as more people decide to follow the trend (i.e. jump on the bandwagon).

When people seek to align their beliefs and behaviour with a specific group this is also called herd instinct. For example, people may purchase a new electronic gadget due to its popularity within their peer group, not because they necessarily need it.

The bandwagon effect is an important driver of behaviour as people align their beliefs and actions with others as they prefer to conform or they derive information from others. Indeed, research indicates that many purchase decisions and behaviours are the result of social influence. For this reason displaying evidence of social proof can be a very effective strategy for establishing trust and credibility for an online brand.

Copy, Copy, Copy:

Mark Earls, author of Herd, suggests that because people are “super social” we naturally copy the behaviour of others, often without even being conscious of it. Few ideas are new and so rather than reinvent the wheel people naturally copy others when they believe it will be beneficial.

Earls argues that social learning as he calls it helps to spread ideas, products and behaviour through our social networks. It is also a major reason for the success of the human race because it allows people to pass ideas and knowledge onto future generations without the need for them to be reinvented. Further, because people often makes mistakes when copying an idea or behaviour this can sometimes lead to improvements that are then copied by other people and become adopted as a new idea.

Asset bubbles:

This bandwagon effect is also seen during stock market and asset bubbles where people stop using their own judgement and rely on the wisdom of the crowd. People wrongly assume that other investors must have knowledge they don’t and also they seek to avoid regret (which they might feel if they don’t follow the crowd).

There is also some evidence in politics of the bandwagon effect with undecided voters choosing to support the party with most popular candidate because they wish to be associated with the biggest party.

Evolutionary Advantage?

Some psychologists also believe that the bandwagon effect may be an evolutionary strategy for reducing the risk of making a poor decision. Being part of a large crowd can certainly provide protection in dangerous environments. Merchants also risk losing reputational capital if they sell sub-standard goods or services to a member of a large group. People understand this and so assume that they are less likely to be ripped-off if they buy from a well-known supplier who is known to other members of their social network.

What conditions make it go viral?

In his book, The Tipping Point, Malcolm Gladwell suggests that for something to spread widely through a population there need to be three types of agents involved. These are connectors, mavens and salespeople.

  1.  Connectors are people with an innate ability to form and maintain long-term relationships with a diverse range of individuals.
  2. Mavens are people who love collecting and sharing specialist knowledge, and have the necessary social skills to pass the information onto others.
  3. Salespeople are very expressive and adept at persuading people through both non-verbal and verbal cues. Indeed, Gladwell suggests these people are much more emotionally contagious than the average person.

However, even with all these agents being aware of an idea or behaviour it will only spread effectively if it is what Gladwell calls “sticky”. This means that the message is memorable in a way that engages and motivates people to share it. Only when this condition is met are we likely to get the kind of behaviour needed to result in a geometric progression which characterises a viral episode.

This may explain why companies with a strong customer-related purpose or personal crusade tend to perform better than the average because people who hold the same passion and beliefs are more motivated to share their brand with others. The insight here is not to focus on influencing a particular type of individual, but instead find your purpose idea and live it.

When an idea or trend gets to a certain point in popularity (known as the tipping point) an availability cascade forms which results in a sudden and huge increase in the adoption of the item. Gladwell suggests that what triggers a cascade are not large changes in behaviour or circumstances, but lots of small changes that amplify the trend. So don’t look to create a large splash, but instead work on generating lots of small ripples and hope they may trigger something bigger later on.

The bandwagon effect & conversion optimisation:

Developing a compelling purpose-led value proposition is an important first step in using the bandwagon effect to improve conversions. It is not what you say about your brand that matters, it is what your customers and staff say that determines what your brand stands for. By having a clear purpose and aligning your businesses’ and staff’s behaviour with what is important to your customers you are more likely to motivate visitors to interact and share your brand with others.

Example of Celebrity Endorsement

Image of cristiano ronaldo playing poker
Image Source: PokerStars.uk

Secondly evidence of social proof can help online conversion optimisation. This includes customer testimonials, celebrity testimonials, number of customers, product rating and reviews, social media likes and shares, awards and brand logos of well-known customers or partners. Indeed, a lack of social proof is often a key reason for poor online conversion rates as visitors are reassured when they perceive that a site is popular and trusted by many customers.

Example of Social Proof A/B Test

Example of A/B testing customer numbers for social proof

In the above A/B test example the only difference between the two variants is that we changed the number of monthly players from all players on the left (i.e. total number of players for all rooms throughout the whole month) to the number of unique players (i.e. only counting each player once in a month) on the right. This dramatically reduced the number of active players that could be quoted underneath the call to action button. Variant B which displays the lower number of unique monthly players reduced registration conversion on the landing page by 5%.

Conclusion:

The bandwagon effect is one of the most important drivers of conversion and sustainable growth. Like any strategy for improving conversion it is essential to establish a strong and compelling base (i.e. a purpose led value proposition) first. This will help to encourage interaction with your brand which facilitates the sharing of your idea or product through social networks.

Having clear evidence of social proof on your site or app should also be a priority as it provides reassurance to visitors that you are a popular and trusted brand. Use online experiments to validate the implementation of social proof as it is particular sensitive to how and where it is communicated.

Related posts:

Herd instinct – Are most purchase decisions the result of social influence?

Herd instinct – How do social networks influence human behaviour?

Herd instinct – What makes social networks tick?

Word of Mouth – 6 myths about word of mouth marketing.

You can view my full Digital Marketing and Optimization Toolbox here.

To browse links to all my posts on one page please click here.

  • Neal has had articles published on website optimisation on Usabilla.com  and as an ex-research and insight manager on the GreenBook Blog research website.  If you wish to contact Neal please send an email to neal.cole@conversion-uplift.co.uk. You can follow Neal on Twitter @northresearch, see his LinkedIn profile or connect on Facebook.

How is AI Disrupting Conversion Rate Optimisation?

Using Evolutionary Pressures To Optimise:

Digital marketing is a zero-sum game – it’s survival of the fittest. Brands have to respond to changing customer needs and pressure from competitors or they go out of business.

What if you could use these evolutionary pressures to automatically adapt and adjust your site according to what has the highest conversion rate? And if your audience changed, perhaps due to a TV campaign, wouldn’t it be great if your site responded by optimising your user experience for the new audience profile? But rather than only improving a single page, what if it could simultaneously optimise multiple pages in the user journey?

Well, with the advent of AI and evolutionary algorithms this time has arrived! Sentient, a company born out of the minds that developed the technology behind Apple’s Siri, has come to market with Ascend. Sentient have combined evolutionary computation (a form of AI which uses mechanisms inspired by biological evolution), and deep learning to create a market leading optimisation solution. What is unique and exciting about Ascend is that it is capable of autonomous decision-making to assist businesses improve their bottom line and enhance the customer experience at the same time.

 

What are the benefits of Ascend?

Sentient Ascend is the first testing and optimisation solution developed by integrating AI, evolutionary algorithms and deep learning technology. As a result it has the capability to revolutionise how testing and optimisation is carried out. The main benefits of Ascend are:

  • Massively complex multivariate tests that have over 1 million possible combinations can be completed with Ascend that would be impossible with traditional MVT solutions. Below is an example of the kind of test that is now feasible with Ascend.

 

Image of multivariate test with over 1 million possible combinations
Source: Sentient Ascend

 

  • Ascend requires lower traffic levels than traditional optimisation solutions because it uses what it discovers about the performance of a particular combination of elements to predict how that combination will influence the conversion rate in the future.
  • Testing is completed with greater speed and double digit uplifts in conversion rates are normally achieved within the first 2 months of employing Ascend. Recently completed tests have achieved between a 12% and 48% uplift in conversions.
  • It can optimise multiple pages simultaneously to improve conversion rates throughout a user journey.
  • Indeed, for underwear brand Cosabella, Ascend tested 15 different changes to the homepage header, category page, product page and shopping cart design. Using standard multivariate testing would have required 160 tests, instead of the automated process that Ascend manages for you. This improved conversions by 35% compared to the control experience.
  • Automates the testing program so that once all your ideas have been input into Ascend it employs all the power of AI to adapt and respond to user interactions to identify the best performing combination of changes to your site or web app.
  • It allows for tests to be paused and new ideas to be input into the testing program as and when required.
  • Automatically adapts to a change in the visitor audience profile without the need for any manual intervention.

How does evolutionary computation work?

To give the evolutionary algorithm a purpose it is first necessary to define a fitness measure. With conversion rate optimisation (CRO) the fitness measure should be the conversion metric that you wish to optimise for such as sales, revenues, average basket value, first time deposit or sales leads. It is important to take care in selecting your fitness metric because it needs to be a characteristic that makes one experience (or algorithm) better than another.

With an evolutionary algorithm each page (i.e. a selected combination of elements) is classed as a genome and it uses genetic operators (i.e. selection, mutation and crossover) to create and maintain genetic diversity. In the example below two high performing pages (see column on the left) have been identified through selection (i.e. survival of the fittest).

Image of how Sentient Ascend uses evolutionary algorithms to optimise designs
Source: Sentient Ascend

However, a further generation of solutions can then be created through crossover (i.e. recombining elements from the two high-performing genome) to create children; the middle solutions above. Mutation (i.e. randomly altering one element in the child’s chromosome) encourages diversity amongst solutions and seeks to prevent the algorithm converging to a local minimum by avoiding solutions becoming too similar to each other. This is shown in the right column above.

Although each operator individually seeks to improve the solutions generated by the algorithm, the operators work together with each other to create an optimal solution that would not be possible if they were used in isolation of each other.  In the first instance the algorithm simply evaluates each page (i.e. genome) to identify if it performs well enough to be a parent for the next generation. Otherwise it will be rejected.

Image of illustration of how an evolutionary algorithm works

This allows literally thousands (out of millions) of experiences to be tested in a short space of time. But as Ascend learns which combination of elements create the best performing designs it automatically adjusts experiences according to how visitors respond. Below is an example of changes that Ascend can evaluate as part of single multivariate test.

The advantage of this technology is that it can create page designs that convert better than those designed by people because it automatically searches for unexpected interactions between elements. It is also doesn’t suffer from human misconceptions or biases, which means that it can generate surprising ideas that we might never have thought of ourselves.

What’s the catch?

Like any optimisation software Sentient Ascend relies on the quality of ideas and designs to generate uplifts in conversion. It is therefore essential to invest in the people who will be using Ascend to ensure they have the required skills and support to get the most out of this amazing solution.

To generate a sufficient quantity of ideas and designs for testing will take some time and resource as you are essentially compressing twelve months or more of testing into a single month or two. This is an analytical and creative process and so it will require the input and approval from various stakeholders if it is to be a success.

To keep Ascend fed with additional ideas after the initial test will also require further planning and support to ensure you get value for money from the solution. There is certainly a danger that rather than focusing on quality hypothesis users might be tempted to throw every idea into the mix without proper evaluation and prioritisation. This would be a recipe for a sub-optimal result as with any model if you put garbage in you will get garbage out.

As with any multivariate test it is advisable to run an A/B test to validate the winning experience. However, no worries, Ascend can manage this for you or you can use your existing A/B testing solution to conduct the experiment.

Conclusion:

Sentient Ascend makes most existing testing software obsolete because it offers an automated platform for massively multivariate conversion optimisation. This allows you to test an enormous number of ideas in a shorter time period than is possible with existing solutions. It is also more efficient at discovering new combinations of elements that result in uplifts in conversion due to the evolutionary nature of the algorithms.

Further, as you can add new ideas as you test you don’t need to wait for the test to end to respond to changes in campaign execution or strategy. You can just keep testing continuously if you have the ideas.

Thank you for reading my post and if you found it useful please share using the social media icons below.

You can view my full Digital Marketing and Optimization Toolbox here.

To browse links to all my posts on one page please click here.

  • Neal has had articles published on website optimisation on Usabilla.com  and as an ex-research and insight manager on the GreenBook Blog research website.  If you wish to contact Neal please send an email to neal.cole@outlook.com. You can follow Neal on Twitter @northresearch, see his LinkedIn profile or connect on Facebook.

 

How Smart is Your Approach to Conversion Rate Optimisation?

Conversion rate optimisation co-ordinates:

 

 

How smart or dumb is your approach to conversion rate optimisation?

I’ve previously written about mistakes companies make with website optimisation where I outlined some fundamental errors that some organisations make with implementing digital optimisation programs. I have also written about strategies for successful conversion rate optimisation programs.  But I’ve not looked at strategies from a clever/stupid perspective before.

Really clever – sounds stupid:

Do you need a user acceptance testing (UAT) team? Not if you ask your developers to test their own changes to make sure they get them right first time and then A/B test the change before they are fully rolled out. This makes developers more accountable as they can’t rely on the UAT team to identify bugs.

Take most of the control for tactical changes to your sites away from the highest paid person opinion’s (HIPPO) and committees by agreeing to use online experiments to inform teams about the effectiveness of proposed changes.

To short-cut building your own internal team consider bringing in expert consultants who have the experience and credibility to shake the organisation up and get things done.

Sounds stupid – Really stupid:

Changing content is not optimisation, it is content management, but it is often called optimisation by some marketers.

When you have more than one digital brand the last thing you should do is to allocate separate optimisation resource to each site/app.  Why test on a small brand with little traffic when you can complete the same test much  more quickly and with a higher degree of confidence on a larger, more profitable brand? This happens though.

Vanity metrics, such as likes and shares are meaningless if they don’t impact on the bottom line.  Monitoring such metrics results in the cobra effect which is damaging to the business.

Optimising each site separately is inefficient and leads to duplication of effort. I call this the Homer Simpson effect – doh!

Usability testing is just common sense. But focus groups are not usability testing and so don’t use them! Enough said.

Sounds clever – really clever:

With the development of AI solutions and evolutionary algorithms it is now feasible to optimise the whole customer journey at once.

Establishing a culture of experimentation and learning through testing ideas out should be a given.

Having a central team of CRO experts who work closely with stakeholders and seek input from the wider business is the most efficient and effective way of using such expertise.

Diversity of people and inputs is key to a successful innovation and change management program. CRO needs to be a collaborative process as that is what it is.

CRO needs senior people with clout to manage all the crap of the highest paid person’s opinion (HIPPO) and the internal politics generated by trying to use evidence rather than subjective opinions to make decisions.

Sounds clever – Really stupid:

Trying to control everything is a stupid and unrealistic idea for anything. To develop a culture of experimentation it is necessary to seek ideas and help from all parts of the organisation.

IT won’t solve optimisation – it needs the support of the whole organisation.

Keeping experiments secret and not circulating results just limits the organisation’s ability to develop the right culture.

Relying on departmental specialism ignores the expertise of conversion rate optimiser’s who bring together skills from number of disciplines. Very stupid approach to optimisation.

Listen to customers, they are your most important stakeholders, but don’t take what they say literally or do what they ask without first testing the idea to measure real behaviour. People are poor at predicting their own future behaviour because the choice architecture influences decision making (volition) and there are many complex and contributory factors that influence the final outcome.

Why on earth would you want to stop testing at peak times? This is when you have most traffic and greatest potential to improve revenues. With high traffic levels you can also complete tests more quickly than at any other time and so you would have to be stupid to waste this opportunity.

Thank you for reading my post and if you found it useful please share using the social media icons below.

 

You can view my full Digital Marketing and Optimization Toolbox here.

To browse links to all my posts on one page please click here.

  • Neal has had articles published on website optimisation on Usabilla.com  and as an ex-research and insight manager on the GreenBook Blog research website.  If you wish to contact Neal please send an email to neal.cole@outlook.com. You can follow Neal on Twitter @northresearch, see his LinkedIn profile or connect on Facebook.