Sticking around

Bad numbers

Nothing obsesses start-up team members and their backers of an app vendor more than revenue and stickiness.

According to the Localytics research report into Mobile App Abandonment of 2016, 23% of users abandon an app after a single use. An interesting additional insight gleaned from this data-set was the positive role in-app messages have.These messages improve users retention to 46 percent, the study found. Localytics found that 17 percent will only use app once if they see an in-app message, but those apps not using messages see 26 percent of users abandoning them after one session. More on this later. For now let's examine some more grim statistics.

A related study report discovered that 84% of user mobile usage time is devoted to a mere 5 native apps. In the UK interestingly enough Whatsapp breaks all the rules. Forty-one percent of UK adults use the app for just over 8 hours per month (or about 2 hours per week). That is longer user engagement than for any of the other top 10 most popular apps that UK consumers use on their smartphone; this includes Facebook, the most popular app, which keeps smartphone users engaged for a little over 90 minutes per week. In the USA, communication and social apps account for 21% of all smartphone minutes. You don't have to be a Harvard MBA to realise that the pie chart from the Forrester Research Report into Mobile Behavior is not exactly encouraging for smaller vendors when it comes to user time share.

Unsurprisingly, the tech giants own your mobile time. Facebook, for example, accounts for 13 percent of U.S. minutes spent on apps, followed closely by Google at 12 percent.

In better news for those of in the fintech space A Forrester Mobile Behavioral Data Report from the UK

revealed that more than half of the 18-24 year old UK smartphone owners use finance and banking apps. Why? The research didn't extend to motivation and intention to use. I'd hazard an educated guess that transactional utility is first and foremost in terms of popularity; simple, important things done well without the need for a lot of cogitation underpinned by the seamlessness and transparency of digital currency. But like everything else in this space it could be better understood with some considered research.

Given this discouraging diagnosis of app persistence what can be done to improve it?

By the way, what exactly is loyalty, the driving force behind app stickiness?

Stickiness & loyalty

Stickiness consists of two dimensions:

the length of time consumers spend on a website, and the extent to which users return to a system (Lin, 2007).

The same author  was able to simultaneously tie both the dimensions of stickiness (duration of visits and repeat visits) to intention to transact via a website

Localytics.com defines its stickiness parameters and metrics as follows:

Engagement As measured by Power Users – the percentage of an app's users who have 10+ sessions in a month (i.e. how many highly engaged users an app has).

Retention As measured by Loyal Users – the percentage of an app's users who return to the app within 3 months of their first session (the industry benchmark to measure loyalty and churn).

App Stickiness = Average of an App's Engagement and Retention (Localytics)

But what underlies the individual user's proclivity to opening, using, continuing to use and perhaps encouraging others to use a particular app? Is is product feature set, design aesthetics, underlying utility, pricing or just plain acquired comfort and sloth?

Furner, Racherla and Babb (2015), developed a framework of how various app features are likely to affect consumers' perceptions of interactivity and developed a set of testable propositions related to mobile application stickiness (MASS). A key plank to the Furner, Racerla and Babb propositions is the role app interactivity plays in stickiness and in particular the design factors of control, communication and responsiveness. Specifically, the role that active control by the user, app responsiveness and perceived personalisation play require research and testing.

Front of mind

Business convention tells us that once we find a market segment and deliver a product or service with the best possible value and needs satisfaction then we should look to assiduously differentiate it from competitor offerings - relentlessly. According to the MBA-types by doing this we are ticking all the right boxes for creating a competitive presence. This principle has been largely founded on a belief that individuals act rationally and think through their consumption choices. Instead basic behavioral science will tell us we instead rely on ingrained preferences and pre-shaped notions, opinions and thoughts when making decisions through a cognitive process known as process fluency. 

As (Lafley & Martin, 2017) explain it

 

..... repeated stimuli have lower perceptual-identification thresholds, require less attention to be noticed, and are faster and more accurately named or read. What’s more, consumers tend to prefer them to new stimuli.

Of course, this inherent decisional laziness of our minds puts incumbent brands in the box seat and the ascendant mega tech names dominate the app landscape as a consequence. Let's face it the ubiquity of Google-Facebook and their empire is almost all pervasive. This default automaticity of app choice continually reinforces a cumulative advantage to the large vendors. This kind of dominance pushes innovators to the brink of ingenuity as they seek to disrupt and hopefully dethrone based on a quantum leap in utility, price and or value. But they have to do more than that if they are to sustain any kind of nascent initial advantage and that push should be into habit-formation centred on the app. This habituation has to be at the speed of light given the tight cash flow runways newcomers operate from.

Engaging behavioral design specialists as part of your core team is a smart first step in creating a habit-forming app.

Give yourself a fighting chance

Lafley & Martin provide 4 key strategies for vendors looking to create cumulative advantage and capitalise on process fluency, I have 2 of more own app-specific principles:

1. Get popular- fast

The old marketing rule of wining early and pricing aggressively holds true in the digital space - hence the explosion of the freemium model. Although more could be done in tweaking this model around for example doses and transaction bundles as well as shorter, more flexible time windows for paid-variants.

2. Design for habit

At least pay heed to formulaic guides from the likes of Nir Eyal and remember brand design elements that ensure your app is easy to find, stands out from the crowd and delivers a consistent user experience that is tailored to the individual's needs. Make the most crucial tasks effortless and the UI with all of its elements inviting, consistent and requiring little thought or ability to use effectively.

3. Innovate from within the app ecosystem

If you do manage to carve a sustainable niche then any variants of the original IP that you conjure in response to validated opportunities should be extensions of the marque including design and service elements.

4. Keep supplementary communication clear and simple

If your app makes saving on power bills quick, easy and painless then don't deviate yor content from that. On-boarding, feature delivery and support services are enunciated using the same constrained lexicon and deliberately curated visual gallery time after time after time. Your users have no time to second guess you. Be predictable, be valuable and don't make them sweat on anything especially changes.

5. Consider playing on a different ground

Could your app play out as a B2B offer via salesforce.com ? Is mobility essential; could you be delivering SaaS as a web-only offer? Dance with the devil and try on Facebook as a 3rd party vendor? Pick the grounds on which you fight and pick it to your advantage and bear in your mind your limitations.

6. Know when they change - stop guessing

Process fluency and cumulative advantage are a given with consumer usage behavior but the individual user will to a greater or lesser extent adapt to a level of contentment until and unless there are environmental changes that motivate them to seek more or different utility.

To monitor these alterations it's worth considering a pre-emptive strategy that pivots around occasional re-assessment of user behavior profiles and motivation not just feature-based satisfaction. Segue this into the UX and secure an evidence-based approach to preventing abandonment. In practical terms, augment the usual app-interactivity metrics with standardised scales administrated through the UI to find out in terms of the app meeting needs and changes. Don't discount the integration of real-time sentiment analysis to gauge contentment trends and rationale.

You know where to find me if you want some practical advice in implementing these principles @mortonandlawson

References

Furner, C., Racherla, P. and Babb, J. (2014). Mobile app stickiness (MASS) and mobile interactivity: A conceptual model. The Marketing Review, 14(2), pp.163-188.

Furner, C., Racherla, P. and Babb, J. (2015). What We Know and Do Not Know About Mobile App Usage and Stickiness:. International Journal of E-Services and Mobile Applications, 7(3), pp.48-69.

Hogan, S., Sides, R. and Kemp, S. (2017). Today's relationship dance What can digital dating teach us about long-term customer loyalty?. [online] Deloitte University Press. Available at: https://dupress.deloitte.com/dup-us-en/deloitte-review/issue-20/behavioral-insights-building-long-term-customer-loyalty.html [Accessed 10 Jul. 2017].

Lafley, A. and Martin, R. (2017). Customer Loyalty is Overrated. [online] Harvard Business Review. Available at: https://hbr.org/2017/01/customer-loyalty-is-overrated [Accessed 10 Jul. 2017].

Lin, A., Gregor, S. and Ewing, M. (2008). Developing a scale to measure the enjoyment of Web experiences. Journal of Interactive Marketing, 22(4), pp.40-57.

Lin, J. (2007). Online stickiness: its antecedents and effect on purchasing intention. Behaviour & Information Technology, 26(6), pp.507-516.

Uncles, M., Dowling, G. and Hammond, K. (2003). Customer loyalty and customer loyalty programs. Journal of Consumer Marketing, 20(4), pp.294-316.

Dr Daryl Foy

Dr Daryl Foy is a Behavioural Scientist who specialises in the design of effective health behaviour change apps based on evidence including his own validated models for optimising persistent use. He consults to industry on how-to integrate persuasive design into LEAN product development as well as conversational UI. He can be contacted at dlfoy@mortonlawson.com