Pufetto — a Ukrainian furniture brand — has an online customization tool where you can build your dream couch changing its size and fabric. But what fabrics are the most attractive? I picked a bunch of popular couches and looked at which fabrics people clicked the most. Below I show how to visualize it with R.

Building a product heatmap

The idea was to build a heatmap showing most clickable fabrics by couches. To make the plot less messy, I included only fabrics that received a minimum required number of clicks. Here is what I got

Looks interesting, but not readable, and definitely not actionable. I decided to improve the following:

1. Limit number of fabrics to top 5 per couch
2. Use relative ranking instead of absolute number of clicks to make fabrics differentiate across couches
3. Sort fabrics and couches by popularity
4. Add meaningful axis labels

Here is the final iteration

Looks much better!

Here is the R code behind it:

# fabric_clicks  is a DF of couch names, fabrics, and dates
fabric_clicks %>%
  filter(date >= ymd('2019-01-01')) %>%
  count(couch_name, fabric) %>%
  group_by(couch_name) %>%
  mutate(rank = rank(desc(n)), total_couch_clicks = sum(n)) %>%
  filter(rank <= 5) %>% arrange(couch_name, rank) %>%
  group_by(fabric) %>%
  mutate(avg_fabric_rank = mean(rank)) %>%
  ggplot(aes(fct_reorder(couch_name, desc(total_couch_clicks)), fct_reorder(fabric, desc(avg_fabric_rank)), fill = rank)) +
  geom_tile() +
  geom_text(aes(label = ifelse(is.na(rank), '', rank)), color = 'white') +
  scale_fill_continuous(guide=guide_colourbar(reverse = T), low="#5EB7F8", high="#1A334B") + 
  labs(title = 'Top 5 clickable fabrics by couches', subtitle = '2019`s average', 
       fill = 'rank', x = 'couch\n ← more popular    less popular →', y = 'fabric by avg rank') +
  theme(axis.text.x = element_text(angle = -45))

Conclusion

It supposed to be a solely technical R-devoted post, so don’t expect result interpretation here (although it seems pretty straightforward — all bestclicking fabrics are both the cheapest and the most visible ones). Remember, that often (1) less is more and (2) order matters.