Tag Archives: trends

Thinking about Product Engagement and Retention

The trigger for this post was this interesting tweet

How are Engagement and Retention related?

An inquiry into this question leads to a perspective on how to view engagement for your product. This perspective will help you decide your engagement and retention strategy effectively.

To dig deeper, let’s start by classifying various products into categories

  1. Utility/Productivity
  2. News & Entertainment (Video, Audio, Text)
  3. Messaging, Social Media & Gaming
  4. Transactional/E-commerce & Payments

I’ve tried to club all apps into these four broad categories for simplification. Now you have to identify in which category does your product fall under.

Let’s consider some examples mentioned in the discussion on the tweet above and map them to categories

By virtue of the category to which your product belongs there will be a potential engagement frequency for it.

Potential Engagement Frequency: Number of times a product can be used over a period of time.

* This frequency is for usage of the core product functionality, the same can be increased by adding more features.

Is High Engagement a necessary but not sufficient condition for Retention?

Not really. While Engagement is strongly correlated with Retention, neither is it necessary for nor does it guarantee Retention.

To understand why that’s the case let’s try to list down other Influencing Factors that impact engagement and retention across products

  1. Needs – Jobs to be done
  2. Trends – Shiny new things
  3. Incentives – Offers, rewards and such
  4. Distribution advantage – Availability of good alternatives, network effects

If you look at any product from these two lenses (categories and influencing factors) you would be able to understand if/where does engagement results in retention and where it doesn’t.

Note: Retention is significantly dependent on the products ability to reliably deliver on the core needs and its stickiness

  1. Utility/Productivity – For this category engagement could be a function of frequency of the need and retention would be a function of how much stickiness can the product build (through data, learning curve etc).

    Some apps I use are Evernote, Myfitnesspal and Shazam. I’ve been using these three apps (with varying levels of engagement) for at least three years. While I use Evernote almost daily, I use Myfitness pal weekly when I’m tracking my weight and it’ll sit unused for months when I don’t track my weight.

    In many such cases retention comes because the effort to learn how a new app isn’t worth the marginal improvement you’ll get.

    Evernote's Smile Shaped Retention

    However, in some cases where the the single player mode isn’t that strong, you’ll have to build engagement around other features to ensure top of mind recall and retention

  2. News & Entertainment (Video, Audio, Text) – For this category engagement could be a good indicator of retention as users one used to a platform don’t tend to change as much as long as content quality is maintained and new content (user generated or otherwise) keeps getting added.

    The exceptions could be some paradigm shifts (like storage to streaming or desktop to mobile) or loosening of distribution advantage (people might be engaging actively with proprietary apps on an OS but that could change quickly if other apps surface) but the shift would be gradual so it can be picked

  3. Messaging, Social Media & Gaming – For this category engagement could be a function of trends and retention could be a function of trends, needs (vs wants) and distribution advantage. Games have the highest 30 day retention among all categories (so definitely more engagement). While Games are particularly prone to change of trend cycles, everyone is familiar about how network effects if working in other direction (or Eflactem’s Law as it’s called) can sink a social media company. More on this here.

    One of the biggest examples was a viral apps called Yo. For those who don’t know about Yo, it was a one tap, one messaging app through which users could send a ‘Yo’ to their friends, who could then reply back with a guess what? (Yo). It had great engagement (over 1.2 mn DAUs at one time) for a few days/weeks that people used it but that engagement never translated into retention.

    The task at hand for games is translate high engagement into stickiness by means such as virtual goods, avatars and such to avoid change of seasons churn and for social networks it is to improve engagement and try to convert that into network effects (while improving the product and increasing its scope for potential users)
The Rise and Fall of “Yo”

4. Transactional/E-commerce & Payments – For this category engagement could be a
function of frequency of need and incentives and retention could be a function of
consistency of experience. Here figuring out the ‘Potential Engagement Frequency
and % adoption from that is a good measure. For ex: Uber measures and tries to
improve their share of airport rides (to departure airport and subsequently from the
arrival airport).

For a flight or a hotel booking site say the average user does a transaction after every
3-6 months or more. One way to approach retention for such cases is to see
what’s the average usage frequency of the user and if that’s increased or maintained.
A drop in previous levels of engagement could be a sign of churn. Also, an drop in
funnel conversion rates for a user should be worrying (For ex: Uber on basis of my
rides data might think I take cabs once a week only but if I check for a ride more often
but book only once a week, perhaps my potential engagement frequency is higher and
they should try to improve my engagement per week.

Here an engagement (non incentive driven) is a good indicator of retention.

Another product that I like but use once a year or so is Cashify. The app does the job
well but it’s not a frequent use case so they have to look at retention over a slightly
long period as compared to say an Ecommerce store. They can however try to get their
users who’ve finished a transaction to refer more users.

Key Takeaways:

  1. Identify your product’s category its potential engagement frequency (PEF).
  2. Understand which factors can influence engagement for your product.
    External (trends, wants, temporary distribution edge) or internal (needs, network effect, stickiness)
  3. For Engagement: First focus on internal influencing factors (strengthening core use case experience, data moats, network effects etc) and build on them. In case of low PEF try to increase referrals.
  4. For Retention: Divide users into cohorts basis their engagement wrt the PEF, monitor and encourage their engagement accordingly.
    Try to understand reasons for drop in engagement and fix them through the product as much as possible (product improvement over incentives)

This Point of view (categories and influencing factors) would help us in figuring out how to look at engagement and retention better. Would love to know what do you think?

Credits: Thanks to Navneet Singh for reading the draft and sharing feedback

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Twitter Marketing, or Spamming ?

Twitter being spreading like wild fire is under a lot of experimentation for marketing and since there isn’t a way to advertise or sponsor stuff “Mentions in Tweets” is the way to get eyeballs along with “Treding Topics” and a few other things. Also, since the trending topics started appearing on every user’s home page, the desire to find a spot among top 10 has soared.

Want to get visibility on Twitter ? Get trending, and the way to be trending is by having enough mentions in tweets.

Add this desire to be mentioned in as many tweets(interesting or boring, happy or sad, sensible or nonsense, related /unrelated to the product or company) to the fact that most people will do just about anything to win something for free (especially if it doesn’t ask them to get up from their chairs) and you get a viral campaign like moonfruit‘s.

moonfruit_spam

Apparently there was a similar campaign by SquareSpace a month back but it failed to make it big because it wasn’t offering the phone but a $199 worth gift certificate but I am not complaining as atleast with SquareSpace’s campaign I got saved from the heavy spam attack that Moonfruit campaign led to.  For me the moonfruit campaign is no different from one of those spam attacks in which people randomly started adding some keyword in every tweet, which eventually led to those topics/keywords being in the trending list.

It’s not that I hate all twitter campaigns, for ex: I appreciate Tweetboard’s campaign, asking people to request for Alpha accounts for their service by tweeting(just once) in a given format instead of submiting their email id’s

TweetBoard

TweetBoard

Now that’s a creative and non spammy way to market using Twitter.

Getting back to #SquareSpace and #MoonFruit campaigns, I’d say this isn’t a particularly good way to market because

1) It’s spammy and so all over the place. More than liking I’d hate if everyone in my stream started putting a random keyword in their tweets. There chances of winning something are a lot less than chances of loosing a few followers/friends. I certainly wouldn’t appreciate my company name in tweets like this

moonfruit_sex

2) It’s not a scalable model:  While SqureSpace, MoonFruit and a few more might be able to get some eyeballs because of these campaigns I strongly believe this won’t be a scalable/easily followable model as if more companies start doing this then we’ll  have  a spoiled twittering experince and almost all the trending topics would be full of these promotional keywords which certainly won’t be liked by Twitter and it’s users and would invite some fixes to avoid such things, which’ll in effect led to a reduction in such campaigns.

3) I doubt if there’ll be significant value addition due to such campaigns: Though some of the statistics could look great after such a campaign I doubt if there’ll be a real value add for most companies that do such campaigns. For ex: I doubt if there’ll be a significant increase in moonfruit’s business or more people will start interacting with @moonfruit etc. Most probably the gift hungry crowd that gathered at their doorsteps  would move to a new free gift location in no time, shattering their false hopes.

That’s how I feel about various marketing campaigns on Twitter, what do you think about them ?

Websites have Cultures too….

Ever wondered why different websites despite being of the same genre
appear/feel differently ? or why your own behavior differs from site to site?

Well the case in point being that all websites across the web consciously or unconsciously develop cultures and subcultures just like it happens elsewhere when a group of people interact with each other over a period of time.

Consider the following examples

Case1: Orkut

I’ve always felt that people(ones I know) spend a lot of time “filling the profile info” and often even more time “maintaining/updating profile info regularly”. It might be necessary in some cases but if you are just there to stay in touch with people you know its not necessary at all but still lots of people(old and new) tend to do it.

Case2: Facebook

I haven’t used Facebook much so in this regard the only thing that stands out is “Adding new apps” and “Requesting others to use new apps”. Every time I log in there are a dozen new requests to try new apps and that’s probably because this viral behavior has really got into the users and seems no signs of stopping.

How a Culture gets developed:

Culture development is a two way process. While in most cases it comes downwards from the top in some systems(emergent) it rises bottoms up. Generally the culture developed by the initial users of the site continues to grow with more people joining and unconsciously following the experienced users behaviors thereby strengthening the existing culture.

What can you do about it ?

Either you consciously develop a culture “Top down” in a planned/phased manner or keep an eye on the small/mini behavioral usage patterns, facilitate them and guide them upwards. This can be done by say adding new features or re-designing the existing ones to make them more available. I feel the features to “push out profile updates” to friends and in your face options to “invite friends to use apps” respectively have helped a lot in setting the above mentioned trends.

A simple example of “Top down” culture that I can think of(and I’ve used) is say you have a website and you want the users to upload their profile pictures instead of continuing with the default ones. One way it can work is say if all the initial user(100 or so) have uploaded their profile pictures then someone whose new to the site might upload a picture straightaway and it stays the same way going forward.

This behavior is quite natural and common as most new users don’t want to look new/naive/different, gain acceptability and become a part of the crowd so they’ll follow the established behavior without making much noise. However simple and obvious it may sound if it happens right it can do wonders for a site consider a social networking site(a friend told me about) where almost all users have provided their mobile numbers despite them not being mandatory. Sounds scary but then its not impossible.