How to analyse your rideshare driving week

The problem

Drivers remember individual trips very well.

You may remember the big fare that made the night feel good, the long pickup that annoyed you or the quiet spell that felt like it lasted forever.

But memory is not the same as a weekly report.

To understand what actually happened, it helps to look at the whole week using the data that was recorded.

Why it matters

One unusually good or bad trip can change how a week feels.

A factual weekly view can answer simpler and more useful questions:

• How long was I online?
• How much of that time was engaged?
• How many offers were recorded?
• How many journeys completed?
• How many were cancelled?
• What was the completed fare total?
• What was the known after-fuel estimate?
• What was the average pickup time where it was recorded?
• How many offers were seen per online hour?
• Was all of the week captured, or are there gaps?

Those are facts. They do not require the software to tell the driver what the facts “mean”.

How to work it out

Start with a simple weekly scorecard.

Time

Record:

• online time;
• engaged time;
• time travelling to pickup;
• wait-at-pickup time where known;
• passenger time.

Activity

Record:

• offers;
• completed journeys;
• cancelled journeys;
• offers per online hour.

Money

Record:

• completed fares;
• known fuel/energy estimates;
• after-fuel estimate where available.

Pickup

Look at observed pickup time and wait time.

Coverage

Check whether the week is complete.

Missing data should stay missing. It should not be silently turned into zero.

Compare with another period

A simple current-week versus previous-week comparison can be useful as long as it remains arithmetic rather than a personalised conclusion.

For example:

• £720 this week vs £680 last week;
• 100 offers vs 90;
• 60 completed journeys vs 55.

That is a factual comparison.

Saying “this proves Friday night is your strongest recurring period” would be a different kind of claim. FareWorth’s reporting does not make that personalised prediction or recommendation.

Simple worked example

Illustrative week

A factual summary can say:

• Current week recorded 10 more offers.
• Current week recorded 5 more completed journeys.
• Completed fares were £40 higher.
• Known after-fuel estimate was £30 higher.
• Offers per online hour were 4.0 vs 4.1.
• Average pickup was 7 vs 8 minutes.

Notice what the summary does not say.

It does not say the current week was “better for you”, that one period is a reliable opportunity or that the driver should change their working hours.

Those are interpretations, not simple reporting.

What to watch out for

Missing data can distort the week

If the app was not capturing properly for part of a day, totals may be incomplete.

More money can come from more time

Higher weekly fares do not automatically mean higher efficiency. If the driver worked more hours, that context matters.

One week is not a recurring pattern

A factual week comparison is useful, but one week alone is not enough to prove a personal working pattern.

After fuel is not net profit

Other business costs remain outside that simple measure.

How FareWorth helps

FareWorth’s reporting can show observed Driver Day and multi-day data such as:

• completed fares;
• known after-fuel estimates;
• offers per online hour;
• Data Coverage;
• time breakdowns;
• pickup and wait averages;
• completed and cancelled journeys;
• current and previous week totals;
• multi-week trends;
• factual comparisons;
• history records.

The driver can see the recorded facts clearly.

FareWorth keeps these comparisons factual. It does not infer from them which patterns are reliable or personally meaningful for the driver.

Practical takeaway

• Review the whole week, not just the trip you remember most.
• Look at time, activity, money and pickup together.
• Check Data Coverage before trusting totals.
• Compare periods factually before drawing conclusions.
• Keep “what happened” separate from “what it means for me”.

Weekly comparison