This article is written by Alexander Sarmiento, who has extensive experience in the fintech sector in the Philippines. Alex welcomes comments (ats@antas.co)

My Jedi master taught me to start with the available data, so here are the Play Store rankings over the 90 day period ending 12/31/2019:

(Paying homage to the 90s-excel-chart aesthetic!) Bear in mind a few things…

1: Grab (with its digital banking ambitions) has a ranking app, though in the Maps and Navigation category. So are B2B fintechs (we’ll cover other species in a coming post);

2: I’ve likewise refrained from highlighting digital lenders with less-than-established backers or track records;

3: the rankings are taken from the Google Play Store (which makes sense to monitor first, in a country where Android comprises over 82% of the mobile OS market). They do not reflect Apple App Store performance[i];

4: the rankings are influenced by app store optimization (ASO) efforts (similar to how web search engine results are influenced by search engine optimization, or SEO). Apps that place higher don’t ‘100% of the time’ necessarily possess more downloads (or active users) than those that rank lower. It chiefly means Google’s algorithm scored them like so, based on factors like downloads, keywords, reviews, as well as visual and text elements.

So which apps rule this galaxy?

In the absence of public-domain stats on active users (folks at a fintech I worked with fondly referred to monthly active users or MAU as its “north star”), app downloads are a rough proxy. The Play Store does not publicly disclose exact download counts, distinguish these from active installs, nor provide historicals, however.

What we do have, listed in Table 2, are download count thresholds: 100k+, 500k+, 1m+, 5m+, 10m+, and so on. I likewise include the number of in-store user reviews, also available from Google Play:

Again, these numbers are just rough proxies for actual user engagement and satisfaction. Market intelligence platforms such as SensorTower and SimilarWeb provide detailed data to paying subscribers that can provide deeper context and insight.

For example, SimilarWeb keeps track of “Usage Rank”, which is based on an algorithm that factors in ‘Current Installs’ and ‘Active Users.’ Table 3 shows how the leading players fared in December, for the 28-day period ending 12/28/19:

Here, mobile banking apps see more run. Even as the bottom half of Table 3 continues to be populated by digital lenders.

In the next post, we’ll hyperdrive into the trends and storylines that headline the Philippine fintech space this 2020.

 

[i] iOS installs can comprise more than a fourth of a digital app’s total monthly downloads, as is the case with the mobile offerings of some top-tier banks (which tend to have a larger proportion of affluent customers who can afford premium-priced Apple devices). On the other hand, other players primarily geared to the broader populace don’t even maintain iOS versions of their app (like Home Credit, Tala, and Atome).

[ii] Tables 1-3: data sourced from Google, SensorTower, and SimilarWeb.

Thanks for reading The Low Down (TLD), the blog by the team at Momentum Works. Got a different perspective or have a burning opinion to share? Let us know at hello@mworks.asia.

 

LEAVE A REPLY

Please enter your comment!
Please enter your name here