Thursday, 13 August 2015

Enhancing digital coupon recall and usage

If asked, could you draw the Apple logo unaided?  

Can you remember all it’s simple features?  Is there a leaf or not?  Is there a bite out of it?  Which side?

Given the ubiquity of the logo on our devices and in the media, many of us would be fairly confident we could create a reasonable facsimile of the logo.

Researchers however put this to the test - or more accurately, put their participants memory to the test - and as expected, most participants were confident of their ability before starting out.  However the research showed that despite this confidence, only 1 in 85 actually got all aspects of the logo correct and less than 50% managed to correctly identify the logo when presented with a number of alternatives.

So, despite seeing it every day, we don’t really “see it” - we haven’t really committed it to memory sufficiently that we can recall its detail.  Remembering a logo is one thing, but what if we need to remember something more important.

From a marketing perspective, one of the most important things we need is for consumers to “remember to remember”.  

We’ve created the perfect conditions for the consumer to form an intent, we just now need them to carry that intent out at some future date.  We’re essentially relying on the consumers memory to prompt them at the right time; whether that’s to further research the purchase or to actually go on to buy it.

This ability to remember to remember is termed prospective memory and is basically defined as where an individual intends to perform an action at a later time.  This could be an event based prospective memory such as "give a message to a friend at the next meeting” or could be time based such as "remember to go to the dentist at 10am on Friday”.
As marketers, we rely on a consumers prospective memory for the call to action to be executed and unfortunately we're relying on something that is extremely fallible.  

Despite our reliance on this prospective memory, there has been little understanding of how it works or how it could be improved.  This is changing though and in recent years there has been a real surge in research studies around prospective memory - and this couldn’t come at a better time.

With the ever increasing transition of marketing from paper based coupons to digital, we are potentially removing an important aide to memory recall.

One of the key parts of prospective memory recall has been found to be a target cue.  Using the example of a grocery coupon, where the consumer has seen the offer and made a decision to take up the offer they would traditionally have taken the paper coupon and put it somewhere to act as a cue when at some point later they went shopping.  This may have been within their wallet or purse or next to their shopping list.  The point is, the physical coupon would have acted as a target cue to trigger the intention at the point it was required.

As coupons move digital however, it’s very easy to browse offers in an email or via an app and select which ones you intend to take up, but then the offer is gone; the email disappears or the app remains unopened. For these digital offers, we’re relying on the prospective memory of the consumer to help them remember they signed up to the offer and to then go on to purchase the product at some point in the near future.

There could still be a target cue -  the event of shopping - but even then, if they have signed up to a number of offers, how likely is it that each offer will be remembered.  At this point we’re then relying on the target cue of the product itself - when (if) they see it and that they remember it’s on offer.

We’re putting a lot of pressure on someones prospective memory - to recall they have signed up to offers and to then recall what offers they have signed up to.

So how can we counter this to ensure we more fully link the intent to take up the offer with the activity of shopping.

Well this is potentially a two step process:-
  • First - We need to get the consumer to remember to check for offers so that they can be reminded of which products to look for.  
  • Second - We need to get consumers to do this every time the shop - we need it to become habitual.
It makes sense to start with the second step first as this is the end state we want.  Essentially, we want the process of checking for offers to become habitual for the customer.  When an activity is habitual we don’t think about it directly, it’s just linked into a wider script we have for the parent task.

As an example, when we drive a car, we don’t have to remember to put the key into the ignition or make sure the gear is in neutral, we just do this automatically.  This task is not being held in prospective memory; we don’t have to remember it.  Getting the use of offers routine then and linked into the wider task can help it to become habitual and move it from something that needs to be specifically remembered to something that simply gets done.  Checking the offers available/opted into then allows individual product offers to provide a reminder - a target cue - which can help to prompt the consumer to find and select the product.

Before this can become an habitual activity however, we need the consumer to start doing it and remember to continue to do it. This essentially relies on prospective memory, with the consumer forming an intent to check the offers when they go shopping and to then actually carry this out.

Anything we can do to help strengthen activation of a prospective memory will be key to helping to turn the task into something that becomes habitual.

One approach that researches have showed works well is when people form implementation intentions.  This involves identifying when and where they will execute the intention and what cues will be present - basically visualising themselves carrying out the task.

The research also shows that people better remember to perform a delayed task when the target cue (the trigger) is encountered in the context of an ongoing task associated with the delayed intention than when the cue is encountered in a different context.  To put it another way, someone trying to remember to use a grocery product coupon will be more likely to recall the offer when in the supermarket - if this was the implementation intention - than when they see the product in their cupboard at home.  

The real trick here is what is termed the encoding - ensuring that the thing to remember (the offer) was specifically linked to the right target cue (being in the supermarket) and to the time (when you plan to shop).  

Encoding implementation intentions has been shown to improve prospective memory performance substantially - between 2-4x - so this works.

This linking of prospective memory intentions into a wider task can also help them to become habitual as it ties them to the bigger task such as grocery shopping which is much easier to remember due to more obvious target cues (i.e. empty cupboards!!)

Thinking about the issue with digital offers, it may well be good practice to not only allow someone to indicate their intention to take up the offers, but also to indicate when they will do it.  This could involve them flagging a likely location for the shop and a date when they may carry this out - forming an implementation intention for checking offers and linking it to a wider task of grocery shopping.

Doing this would also have the added advantage of allowing us to switch the prospective memory task from being an event based one (going shopping), for which we can’t influence the trigger cues, to a time based one which we can.  For example, knowing the intended date and time of the shop we could use an additional target cue such as adding a diary reminder to flag up at the agreed time as well as a location based notification when the customer is in the vicinity of the selected store at the appointed time.

Strong target cues which we can control also help to overcome another weakness within prospective remembering - which is that prospective memory is typically impaired when the current task is demanding.  

So if someone is busy doing something requiring a lot of memory based thinking, then it is less likely they will remember an intended action unless the target cue is highly salient.  Using the context of remembering a grocery offer, you could argue that the mere act of grocery shopping in a busy store with kids in tow is a taxing enough task on its own - trying to remember something that was on offer to you 5 days before will be less likely.  However, using time and location based notifications which are closely linked to the broader task of shopping makes it more likely that the intended task - using offers - will be remembered.

Retrieval of the intended task is also interesting as its not just triggered based on target cues - although these are shown to be very powerful.  

Interestingly, in one study by Kvavilashvili and Fisher (2007), they found that when participants were given a task of phoning the researchers back the following week, the participants typically recalled that task over the week around 8-11 times.  Many times this recall was found to be associated with trigger cues related to the task such as seeing a telephone.  However, more interestingly, around 40-50% of recollections were completely untriggered - they just popped into the participants head.

Knowing we recall an intention 8-10 times before its intended implementation could be a useful characteristic if directly catered for within a digital offers solution.

If consumers will randomly remember the need to check for offers a number times during the week, it may be possible to include functionality to reward this recall.  

For example, building in a “need” to review offers in the app - maybe to check for changes such as a better offer - could create a reason to check the offers regularly, helping to reinforce them and also ensuring that any date/time based implementation intention is still correct.

This whole area of prospective memory is still an emerging research area with differences of opinion as to exactly how we remember things and how this could be improved.  That said, given our increased reliance on the consumers memory as we remove physical target cues, combined with our ability to intelligently create new, highly relevant ones suggests this is an area we should pay more attention to as marketers.

Saturday, 11 April 2015

Periscope and Meerkat lead the way on creating a new kind of shared experience

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"What if you could see through the eyes of a protester in Ukraine? Or watch the sunrise from a hot-air balloon in Cappadocia? It may sound crazy, but we wanted to build the closest thing to teleportation."

Rather poetically (and much quoted), this is how new live video streaming app provider Periscope describe their service - one of two new high profile launches of live video streaming apps with the other being Meerkat.

This is not a new market, apps such as LiveStream and UStream have been around for a while.  However, with increasing 4G coverage and investment from the likes of Twitter (they recently purchased Periscope for just under $100m 2 weeks after it launched), this sector is hotting up as the next big thing.

Meerkat founder Ben Rubin describes the trend as "spontaneous togetherness” and this to me is the most interesting aspect of it.

In a media world where everything is available at the touch of a button; TV can be paused and rewound; films are available on demand (and sometimes before they're even in the cinema); the “magic” of TV has been lost.  That shared experience we used to have when a new TV show aired is increasingly becoming extinct.  With so much choice, technology and platforms, people are watching it at different times or even not watching it at all.

Indeed, if you’re in the Millennial Generation, there’s a good chance you never even tuned in.  

Something that hasn’t really made the headlines, is that in 2015 there has been a double digit decline in traditional TV viewing for millennials (18-34).  This has been happening since 2012 with a fall of around 4 percent year on year.  However at the end of 2014 this fell an amazing 10.6 percent.  Overall this has translated as almost 20% fewer young adults watching traditional TV than 4 years ago.

Alan Wurtzel, NBCUniversal’s audience research chief is quoted as saying:-

“The change in behavior is stunning. The use of streaming and smartphones just year-on-year is double-digit increases […] I’ve never seen that kind of change in behavior.”

This doesn’t mean of course that they’re not watching video content, it’s just not the content that the media industry wants them to watch.  Instead, they are reportedly watching 11.3 hours of “free” online video per week and interestingly the major ways young people are selecting online content to watch is based firstly on content that has been viewed/liked by a lot of people (59%) and secondly content that was sent by “someone I respect” (58%).  

So no surprise - peoples viewing habits are now more likely to be influenced by their personal social network.

This is where both Periscope of Meerkat have a distinct advantage.  They both tie into twitter as a means of making people aware of live broadcasts and given that tweets are heavily influenced by the people you’ve chosen to follow, these broadcasts are more likely to be relevant to the viewers.

But it goes further than this.  These are not static video feeds like you see on Youtube, instead the audience is positively encouraged to participate, to help direct the production.  

In an article on the Verge they reported that "In their early tests [of Meerkat], they found something delightful in the interactions between the broadcaster and their audience: the audience always wound up helping direct the broadcast with their comments, to the general enjoyment of everyone involved”… and this is where the “spontaneous togetherness” comes in.

There is something powerful about being in the moment; this ephemeral experience which can only happen at that time, which places you at the centre of the action, allows you to take part and which happens within your social network - this could be a truly compelling mix.

Having played with Periscope, it’s funny how much it differs from a traditional pre-recorded video stream.  Even when the vloggers have created tailored content for their audience and speak to them like a personal friend, its still not as compelling as actually being in the moment.

It’s like we’ve gone back to that shared experience, but at a hyper relevant level.

So whats the implications for loyalty marketing?  Well I’ve no doubt that marketers generally will find ways to create “brand engagement” and “brand experiences” through live videos - whether product launches, celebrity moments or just regular brand ambassadors creating content to watch and interact with.

What I think will be interesting though is if that personal connection - that in the moment experience - becomes as common place as the Facebook wall-post or the Tweet.  If that happens, people are going to have greater expectations of their interactions, whether personal or business.  Imagine what online banking looks like through live video streaming or being able to access customer service at your online retailer through video.

In fact, stop imagining it as that’s what Amazon has already done with it’s Mayday button on the Kindle Fire, launched in late 2013.

Described by CEO Jeff Bezos as “the greatest feature we’ve ever made”, they may truly have hit on something at the beginning of a new trend.  As consumers are conditioned by apps like Periscope and Meerkat to want “real” connections, you can imagine them increasingly seeking out brands that provide a similar experience.

Amazon is reportedly fielding 75% of questions from Kindle Fire customers through Mayday with questions ranging from how to beat a level on Angry Birds to singing Happy Birthday to a new Kindle Fire owner.

Loyalty is all about customer experience and it would seem that what Periscope, Meerkat (and Amazon) are showing is that a new kind of customer experience can be created.  One centred around real moments of truth in real time.

 

 

 

 

 

 

 

Tuesday, 13 January 2015

Loyalty - Building a better mousetrap

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Ask someone how many loyalty programs they are a member of and they can probably name 3 or 4 big programs they use regularly. However, in the US, loyalty program membership is now over 23 per household and between 2008 and 2012 it grew by 10 percent per year. These are great numbers until you realise that only around 1/3 of these memberships are being actively used.

More worryingly, a study by McKinsey back in 2013 suggested that for many companies, those with loyalty programs actually underperformed vs the market with “loyalty-focused companies surveyed [growing] revenues at a weighted-average rate of 4.4 percent per year – compared to 5.5 percent for companies with lower loyalty focus.”

This doesn’t mean loyalty doesn’t work – it does and McKinsey acknowledge that. What it does mean though is that like anything, there is no quick fix; no silver bullet. A “me too” loyalty program is likely to add little long term value if it isn’t designed well and there are all too many of these in the market.

However, what is interesting is that when talking about what a good loyalty program looks like, the discussion frequently looks at program features like partnerships or reward value without really considering what actually makes a loyalty program work – and why they also fail.

If we can understand what makes someone use and continue to use a loyalty program - what’s going on in their brain - then we can truly design a program that works harder and is more rewarding.  As the famous quote says “Build a better mousetrap and the world will beat a path to your door"

A good place to start with this mousetrap is back in the month of May, 1938, in a cold Minnesota that had just experienced one of its heaviest snowfalls ever for that month with over 12 inches of snow falling in just one day. That same month, psychologist B F Skinner published his now famous book called The Behaviour of Organisms – and it’s that book, published almost 80 years ago which provides some answers as to both why loyalty programs work, and why they don’t.

Before discussing that though, it’s worth also considering something happening in the here and now.

Consider for a moment how often you check your phone for new email or to check your Facebook account. Whatever number you come up with, you’ll probably be way off the mark because half the time, we do it almost on auto-pilot. One article suggests we check our phones over 1500 times per week - thats more than once every 5 minutes during waking hours.

It’s not just the checking however, we are also at the beck and call of these devices.  

A research study by Loughborough University in the UK found that people, on average, take just 1 minute and 44 seconds to respond to a new email notification - with 70% of these alerts getting a reaction within 6 seconds and 85% within 2 minutes.

We talk about the mobile phone being the remote control of life… it could equally be said that the mobile phone is actually the remote control of us.

What this all means however is that we are essentially re-wiring our brains.  Our brains are wired to protect us from danger or to help us survive; when we see something in the corner of our eye we respond. This is known as our orientating responses and these are now constantly being triggered by the ping of a mobile or the flash of a notification meaning we’re becoming ever quicker at responding and anticipating a response.

There is more to this phenomenon however and this is where that cold May in Minnesota comes in.  

The book published by B F Skinner introduced the world to the concept of operant conditioning.  Simply put, operant conditioning describes any voluntary behaviour that is shaped by its consequences and it implies a creature (including you and I) will repeat an activity that produces positive rewards.  Underpinning this operant conditioning are a number of reinforcements which, when repeated, serve to further in-grain the behaviour.

Skinner based his research on observing animals such as rats and pigeons, which when placed into a specific environment (known as the Skinner Box), would carry out a repeated behaviour based on the rewards offered (i.e. press a lever to get food).  Using this environment, Skinner was able to vary how and when the reward was delivered in order to measure the ability to influence and maintain ongoing behaviour - called a positive reinforcer.

From this research, Skinner came up with three schedules of reinforcement, defined as continuous, interval and ratio based.

  • Continuous - Defined as a constant delivery of reinforcement for an action; every time a specific action is performed, the subject instantly and always recieves a reinforcement.  With this type, the reinforced behaviour is prone to extinction and the behavior can become inconsequential (i.e., producing neither favorable nor unfavorable consequences) and so starts to occur less frequently
  • Interval - Based on the time intervals between reinforcements.  These can be fixed time periods (FI) or variable (VI), with the variable being based on an average time that has passed since the last reinforcement.  Both of these are not directly linked to the persons actual behaviour and so typically produce slow, methodical responses.
  • Ratio - Can be based on the behaviour of the person and be fixed or variable too.  The fixed ratio (FR) is based on a specific number of responses (e.g. Coffee Stamp Card), whereas the variable ratio (VR) is based on a particular average number of responses (e.g Slot machines - pays out 10% of the time on average, but there is no guarantee when).  

Schedule of reinforcement

It’s these reinforcement schedules that are key to understanding why we’re so quick to react and respond to that email notification - and why some loyalty programs work and others do not.

Simplistically, where the reinforcement schedule is predictable, whether by being continuous or at set intervals, then the behaviour becomes in Skinners words “extinct” - so its passive and inconsequential and decreases or stops altogether over time.  On the other hand, where the reinforcement is on a variable ratio - where both the timing and the value can’t be predicted - then we get the highest rates of response and the the higher the ratio, the higher the response rate tends to be.

In the book The End of Absence: Reclaiming What We've Lost in a World of Constant Connection, author Michael Harris highlights this saying "Animals, including humans become obsessed with reward systems that only occasionally and randomly give up the goods.  We continue the conditioned behaviour for longer when the reward is taken away because surely the sugar lump is coming up next time."  This “variable interval reinforcement schedule” is really the critical factor in repeatable, ongoing behaviour.

This outcome can be seen in how we interact with email as discussed previously.  One behavioural psychology training course describes this effect with email saying:-

"Receiving a message serves as a reinforcer, or reward for, checking. You might check your email at 9:00 a.m. and have 5 new messages, at 11:00 a.m. and have none, and then at 3:00 p.m. and have 7. As long as you periodically continue to receive messages, your checking behavior will continue; however, this behavior can be influenced by the number of messages received. If you don't receive any messages for 5 days, you may check less often. On the contrary, if you receive several messages each time you check your email, you will probably check more often. In this case, your behavior is an effect of variable-interval schedules of reinforcement. You receive a reward (new messages) for a behavior (checking your email), and the reward is presented on a variable schedule (you can't predict when it is coming)."

This is also something that the gambling industry relies on to keep punters coming. Co-Author of the book Mind Hacks and lecturer at the University of Sheffield, Dr Tom Stafford discusses this saying:-

"Both slot machines and email follow something called a 'variable interval reinforcement schedule which has been established as the way to train in the strongest habits. This means that rather than reward an action every time it is performed, you reward it sometimes, but not in a predictable way. So with email, usually when I check it there is nothing interesting, but every so often there's something wonderful - an invite out, or maybe some juicy gossip - and I get a reward."

Another industry that uses Variable Ratio (VR) reinforcement schedules is video gaming.  In the research paper “Video game structural characterisitics - A new psychological taxonomy” it describes how powerful operant conditioning techniques can be for players saying:-

“Players respond rapidly and persistently to the reward features in video games, such as XP and points, rare items, and meta-game rewards. These features are core components of the variable reinforcement schedule, which is known to create a persistent pattern of responding to a stimulus over time that is resistant to behavioural extinction."

Video games build on this however using a number of different schedules - continuous, interval and ratio - in a combined way to create what is called a compound schedule which may superimpose two or more different and overlapping schedules to gain maximum effect. Just as a gamer is accomplishing one mission they have already started on another; in this way, using overlapping and compound schedules, game designers keep the players involved which leads to sticky and sometimes "addiction" like behaviours.

In the research study "Understanding and Assisting Excessive Players of Video Games”, authors King and Delfabbro (2009a) found that overlapping quests and objectives (i.e., concurrent schedules of reinforcement) in video games kept players playing for longer periods than games without these features.  The report also detailed how the use of VR schedules could also cause game players to carry out behaviours that are repetitive or boring, simply to chase the reward saying:- 

 “The variable-ratio reinforcement schedules in video games and participants’ need to complete goals often produced what was termed ‘grinding’ behaviour. Grinding refers to the repetition of an action or series of actions in a video game in order to obtain a reward."

Speaking about this behaviour, one player stated how he "played the same level 10 times to get the full set of armour. [It] gets frustrating but you have to do it if you want the items"

This is really interesting because it suggests that the power of the right mix of reinforcement schedules can actually mask the more mundane actions required to achieve it.

Whilst people obviously consider themselves unique and with their own individual decision making processes, the reality is that people tend to respond consistently to the same kinds of environment.  Keeping with the video game theme, it’s interesting that research has shown that it's more about the design of the game mechanics than the individual gamers characteristics that drives usage.  The research paper entitled “The role of Structural Characteristics in Problem Video Game Playing” pointed this out saying:-

"In particular, ‘structural characteristics’, defined as those features that facilitate the acquisition, development, and maintenance of playing behaviour irrespective of the individual’s psychological, physiological or socioeconomic status, have been shown to play an important role in explaining the appeal of gambling activities."

Further examining what makes video games “sticky”, the psychology book Mind at Play by Loftus and Loftus (1983) showed that the appeal of video games was a blend of variable-ratio and fixed-interval schedules which were intended by designers to be “addictive”.  They noted that key aspects of this are that players are:-

  1. Often reinforced almost immediately for correct play
  2. These rewards for good game play are of large [perceived] magnitude (i.e., the provision of 150 points appearing more significant than 15 points)
  3. Rewarded on numerous concurrent reinforcement schedules

So, back to the question at hand - If we can understand what makes someone use and continue to use a loyalty program - like they do a video game - then we can truly design a program that works harder and is more rewarding.

Loyalty programs, in part, already rely on the principle of positive reinforcement whereby when an event or stimulus is presented (e.g. points) as a consequence of a behaviour then the behaviour goes on to increase.  It’s this behavioural psychology that underpins much of the change we see within customer loyalty.

However for the majority of loyalty programs, whether explicitly designed in or not, there is only one reinforcement schedule which is the continuous issuance of points in response to a purchase.  From the customer perspective, every time I buy I get points which is much the same as the animal in the Skinner box which gets food every time the lever is pressed.  

The problem for these loyalty programs is that we already know that this continuous reinforcement schedule is the least likely to result in long term ongoing behaviour - we’re essentially designing in program extinction from the get go.

The second issue is that as previously discussed, our brains are increasingly becoming used to managing constant distraction - honing our orientating responses.  In a world where there is always another notification to respond to, another Facebook post to view, another email to read, any loyalty program has got to be able to cut through to compete with this.  With so many things fighting for our attention, the larger the gap between the behaviour and the stimulus, the more likely our brain will not link these two activities and the more likely we won’t get the full benefit of this positive reinforcement.  

This starts to manifest itself within loyalty program behaviour - customers will typically continue to swipe their card at point of sale because this is a learned (or prompted) behaviour - but it’s done passively.  There is no stimulus driving this current behaviour and so its less likely we’re able to influence it at this point in time.  Trying to get customers to then change or uplift their actual behaviour doesn’t work because there is no linkage between the behaviour and the reward/stimulus - the behavior has become inconsequential.

To create a loyalty program that works for consumers and works for brands, we have to ensure that the ’structural characteristics’ of the program provide a number of different engagement mechanics  - reinforcement schedules - so that we create a persistent pattern of responding to a stimulus over time that is resistant to behavioural extinction

As the research shows, this behavioural design works in gambling and it works in video games - some would argue it works too well.  However there is already evidence that it works within loyalty programs.  Some programs that do work well have many of these characteristics with a good blend of compound schedules.

For example, in a classic frequent flyer program there can be a continuous reinforcement schedule around miles earned for flights, but these are overlapped with fixed ratio schedules such as collecting towards tiering and benefits like companion tickets.  Whilst these are not necessarily using the most powerful variable ratio (VR) reinforcement schedule, they still manage to engage members through compound reinforcement schedules.

This also brings into focus gamification - that new entrant into loyalty program design - and starts to explain why, when implemented well it can truly accelerate program engagement.  Whether expressed as access to time limited deals, unlocking of recognition or achievement of challenges, gamification allows the loyalty marketer to superimpose additional, overlapping reinforcement schedules including variable ratio to gain maximum impact and benefit.  This isn’t just theory either - we’ve seen examples of this whereby simply switching a recognition mechanic from a fixed ratio to a variable ratio has resulted in a 33% increase in ongoing usage.

Yet loyalty programs continue to be launched and continue to under perform.

As loyalty marketers its imperative that we understand why loyalty programs work, why consumers respond to them and how to make them work better for all.   In the words of B F Skinner “A failure is not always a mistake, it may simply be the best one can do under the circumstance.  The real mistake is to stop trying"