The category that eats the chart

channel on saas-subscriptions has 6 values, and one of them is 26.4% of the data.

• organic — 661 rows, 26.4%
• paid search — 436 rows, 17.4%
• content — 425 rows, 17.0%
• referral — 405 rows, 16.2%
• outbound — 307 rows, 12.3%

The top three take 60.9% between them. With only 6 values there is no tail to worry about, which makes this a genuinely easy column to chart.

select channel,
       count(*)                                      as rows,
       round(100.0 * count(*) / sum(count(*)) over (), 1) as pct,
       round(avg(mrr_usd)::numeric, 2)             as avg_mrr_usd
from saas_subscriptions
group by 1
order by rows desc;

The second column is the one that matters. Share of rows tells you what is common; avg_mrr_usd tells you whether the common thing is the important thing. They disagree more often than not, and a chart that shows only the first is answering the easier question.

Decide what happens to the tail before you plot it. "Other" as an explicit bucket is honest; twelve slivers is not, and neither is silently taking the top eight.