14-Day Free Follow-up — Consumer Study

n = 119 · Top 6 metros

Extending the free follow-up window is a wanted, low-resistance change

Follow-ups are a normal part of the patient journey, but the current 7-day free window cuts them off before people are ready. A 14-day free follow-up tests as near-universally appealing and, more importantly, as a genuine reason to choose Practo over an alternative.

69%
often/always need a follow-up (T2B)
50%
say a 7-day window is too short
84%
very likely to use a free 14-day follow-up
88%
say it would influence platform choice (T2B)

The story in five points

  • Follow-ups are mainstream, not edge-case. Nearly 7 in 10 respondents often or always feel the need for a follow-up visit (T2B 69%), and a similar share actually go (T2B 66%).
  • What blocks follow-ups is mostly external, not a lack of need. Among those who don't consistently return, the top reasons are feeling better (70%) and the 7-day free window expiring (55%). A quarter were blocked by doctor unavailability. base 40 — directional
  • There is an explicit unmet need on duration. Half call the current 7-day window short (50% "very"/"somewhat" short), and the average preferred window is ~10 days — comfortably inside a 14-day offer.
  • The proposition itself is highly compelling. 84% would be very likely to use it (97% T2B), and 38% say nothing at all would stop them from booking if it were free.
  • It moves platform choice. 88% say a guaranteed free 14-day follow-up would influence their choice of Practo over another platform or clinic — with 66% saying "extremely". 3 in 5 want the follow-up auto-scheduled at the time of the initial booking.

Study design

Objective

To assess consumer interest in Practo's proposed 14-day free follow-up consultation feature and evaluate its potential to drive adoption, repeat engagement, and platform preference.

Target group

CityTop 6 metros
GenderMale | Female
Age band18–60 years
NCCSA | B
UsershipAny doctor consultation in the last 6 months (min. 70 offline)
Practo cohortsOne-time | Repeat | Aware non-trialist (min. 30 each)
SampleTarget 100 · Achieved 119

Who the 119 are

44%
Practo repeat users (n=52)
31%
Aware non-trialists (n=37)
25%
Practo one-time users (n=30)
Reading conventions used in the source tables: T2B = top-two-box (the two most positive scale points). Bases under 60 are read as directional only; bases under 30 are not reported. All figures are percentages of the stated base unless labelled otherwise.

Follow-up behaviour & the 7-day gap

The need for follow-ups is high and consistent across cohorts. The leak happens between intending to return and actually returning — and the free-window expiry is one of the two biggest causes.

Q8 · Base 119
How often do you feel the need for a follow-up visit?

Follow-ups are a normal expectation, not an exception — virtually nobody says "never".

Always30.3%
Often38.7%
Sometimes30.3%
Rarely0.8%
Never0.0%
T2B (always + often)68.9%
Mean 3.98 / 5. By cohort (T2B): aware non-trialists 78.4% · one-time 63.3% · repeat 65.4%.
Q8a · Base 119
How often do you actually go for it?

Stated behaviour tracks need closely — a 2.5pt gap between needing and going. The intent is there; the friction sits elsewhere.

Always25.2%
Often41.2%
Sometimes32.8%
Rarely0.8%
T2B66.4%
Mean 3.91 / 5. Aware non-trialists claim the highest follow-through (T2B 75.7%); repeat users the lowest (59.6%).
Q8b · Base 40 directional
Why don't you go for the follow-up?

Asked of those who only sometimes / rarely / never return. The barriers are circumstantial and largely fixable by product — window expiry, forgetting, and doctor availability together outweigh "I didn't need it" (7.5%).

I started feeling better70%
7-day free window was over, didn't want to pay55%
I forgot to schedule it30%
Doctor was not available25%
I did not have time20%
Travelling to the clinic was inconvenient15%
Consulted another doctor instead10%
Didn't think a follow-up was necessary7.5%
Multi-select; average 2.33 reasons per respondent. Base of 40 is below the 60 threshold — read as direction, not magnitude.
Q8c · Base 119
How adequate is a 7-day free follow-up period?

Exactly half find it short. Only 9% think it is too generous — so lengthening the window carries almost no perceptual downside.

Very short — want longer than 7 days26.9%
Somewhat short23.5%
Just right — 7 days is adequate40.3%
Somewhat long5.9%
Very long3.4%
Net "too short"50.4%
One-time users are the most likely to call it long (20% "somewhat"/"very long"), repeat users the least (3.9%).
Q8d · Base 119
Ideal free follow-up window, in days

Average preference lands at 9.8 days. 63% want more than 7 days — and a 14-day offer covers 97% of all stated preferences.

Up to 5 days4.2%
Up to 7 days32.8%
8–10 days20.2%
11–12 days17.6%
13–14 days21.9%
More than 14 days3.4%
Covered by a 14-day window96.6%
Mean days by cohort: repeat users 10.1 · aware non-trialists 10.1 · one-time users 8.9. Repeat users skew hardest to the 13–14 day bucket (32.7% vs 21.9% overall).
Q11 · Base 119
How often did you need a follow-up within 2 weeks but not book one?

This is the size of the miss. Nearly half report often or always having an unmet two-week follow-up need — the exact window the proposition covers.

Always12.6%
Often36.1%
Sometimes40.3%
Rarely9.2%
Never1.7%
T2B48.7%
Mean 3.49 / 5. Highest among one-time users (T2B 60.0%) — the cohort most likely to have hit the window and not come back.

Cohort comparison — behaviour

MeasureOverall
n=119
One-time
n=30
Repeat
n=52
Aware non-trialist
n=37
Needs a follow-up (T2B)68.963.365.478.4
Actually goes (T2B)66.466.759.675.7
Unmet 2-week need (T2B)48.760.038.554.1
7 days is "too short"50.446.748.156.8
Preferred window (days)9.88.910.110.1
All cohort bases are under 60 — differences here are directional and not tested as significant unless flagged in the source workbook.

The 14-day proposition

Tested as: “If your consultation automatically included a free follow-up within 14 days…” Appeal is close to a ceiling, and — unusually for a free-benefit test — it converts into stated platform preference rather than just goodwill.

84%
very likely to use it
97%
likely to use it (T2B)
38%
say nothing would stop them booking
88%
would let it influence platform choice
Q12 · Base 119
How likely would you be to use a free follow-up within 14 days?

Only 2.5% are negative in any degree, and nobody is neutral — the concept is understood and wanted, with no fence-sitters to convince.

Very likely84.0%
Somewhat likely13.5%
Neither0.0%
Somewhat unlikely1.7%
Very unlikely0.8%
Mean 4.78 / 5 — the highest-scoring measure in the study. Repeat users are the most enthusiastic (92.3% "very likely"), aware non-trialists the least (75.7%), but every cohort clears 94% on T2B.
Q13 · Base 119
If it were free within 14 days, what would still stop you booking?

The largest single answer is “nothing”. Every remaining barrier is operational — availability, memory, timing, rebooking effort — rather than a rejection of the offer.

Nothing, I would book it37.8%
The doctor may not be available32.8%
I may forget to schedule it31.9%
Timing may not be convenient24.4%
Rebooking is too much effort19.3%
May not feel the need18.5%
Would prefer a different doctor17.6%
Multi-select; 1.45 barriers per respondent on average. Repeat users carry the fewest (1.10) and are far more likely to say “nothing” (51.9% vs 13.3% among one-time users) — one-time users carry the most friction (2.07 barriers each) and are the cohort to design for.
Q14 · Base 119
How should the follow-up be scheduled?

Three in five want it booked for them up front. Nobody has “no preference” — this is an active choice, and it directly answers the “I may forget” barrier above.

Auto-scheduled at initial booking60.5%
Reminder, then book it yourself39.5%
No preference0.0%
Consistent across cohorts (57.7%–66.7% favour auto-scheduling). Note the tension: 32.8% worry the doctor may not be available — auto-scheduling only works if the slot is genuinely held or easily moved.
Q15 · Base 119
Would a guaranteed free 14-day follow-up influence you to pick Practo?

The commercially important number. Two-thirds say “extremely” — the intensity, not just the reach, is what makes this a differentiator rather than a hygiene feature.

Would influence extremely66.4%
Significantly21.9%
Moderately0.8%
Slightly8.4%
Not at all2.5%
T2B88.2%
Mean 4.41 / 5. Repeat users highest (T2B 92.3%, mean 4.56); aware non-trialists are reachable too (86.5% T2B) — the offer works as an acquisition hook, not only a retention one.

Cohort comparison — proposition

MeasureOverall
n=119
One-time
n=30
Repeat
n=52
Aware non-trialist
n=37
Very likely to use (Q12)84.080.092.375.7
Likely to use, T2B (Q12)97.5100.098.194.6
“Nothing would stop me” (Q13)37.813.351.937.8
Avg. barriers (Q13)1.452.071.101.43
Wants auto-scheduling (Q14)60.566.757.759.5
Influences platform choice, T2B (Q15)88.283.392.386.5

What this implies

  • Ship the window at 14 days, not 10. Average preference is ~10 days, but 14 covers 97% of stated preferences at what is likely a small marginal cost — and “14” is the number that tested.
  • Auto-schedule by default. 60% want it, 0% object, and it neutralises the “I may forget” barrier that 32% raise unprompted.
  • Doctor availability is the real delivery risk. It is the top residual barrier (33%) and already blocks a quarter of today's follow-ups. The promise is only as good as the slot supply behind it.
  • Design the flow for one-time users. They carry 2× the barriers of repeat users and are least likely to say “nothing would stop me” (13%) — yet they report the highest unmet 2-week need (60%). That gap is the addressable opportunity.
  • Treat “I started feeling better” as a messaging problem, not a lost cause. It is the single biggest reason for skipping follow-ups (70%) and is unaffected by price.
This section is inference drawn from the data, not statements made in the source workbook.

Audience & market context

A young, affluent, heavily digital metro sample. Read the headline numbers with that in mind: this is the segment most primed to accept a digital-first health benefit, not a national read.

31.9
average age (years)
54 / 46
male / female split
71%
NCCS A
67%
consulted in person (OPD)
Q1 · Base 119
City
New Delhi23.5%
Bengaluru22.7%
Hyderabad18.5%
Mumbai16.8%
Chennai10.1%
Pune8.4%
Q2–Q3, NCCS · Base 119
Age, gender and class
18–24 years0.8%
25–34 years68.9%
35–44 years30.3%
Male53.8%
Female46.2%
NCCS A (A1 58.8 · A2 12.6)71.4%
NCCS B28.6%
Bars in this block are scaled to the block maximum, not to 100%.
Q7 · Base 119
How did you attend your doctor consultations?

Two-thirds are still physically walking into a clinic. The follow-up promise therefore has to work for offline-originated consultations, not just teleconsults.

In person at a clinic / hospital (OPD)67.2%
Video consultation30.3%
Audio consultation1.7%
Chat consultation0.8%

Competitive frame

Practo has universal awareness in this sample and the highest ever-use — but usage is shallow, and four competitors are used by more than 4 in 10.

PlatformAware (Q9a)Ever used (Q9b)Conversion
Practo100.068.969%
Apollo 24|795.865.668%
MediBuddy79.861.377%
Tata 1mg82.458.871%
Netmeds76.541.254%
MFine29.47.626%
Lybrate22.75.926%
Eka Care10.95.046%
Jio Health Hub31.15.016%
Average 5.29 brands known, 3.19 ever used — this is a multi-homing category, which is why a differentiating reason-to-return matters. “Conversion” is ever-used ÷ aware, computed here for reading; it is not a field in the source workbook.
Q10 · Base 82 (ever used Practo)
How many times have you used Practo?

Usage is thin: over a third stop at one booking, and the average is 2.68 bookings.

Only once ever36.6%
2–3 times30.5%
4–5 times19.5%
More than 5 times13.4%
QC · Base 119
Cohort split

Recruited to a minimum of 30 per cohort so each can be read separately.

Practo repeat users (n=52)43.7%
Aware non-trialists (n=37)31.1%
Practo one-time users (n=30)25.2%
Q6 · Base 119
Activities undertaken in the last 6 months

Screener context: an average of 9.7 of 12 digital activities each. Friction-free digital booking is an established habit for this sample, so a rebooking flow is not a novel behaviour.

Consulted a doctor (in-person or online)100%
Used a digital payment app93.3%
Ordered food online92.4%
Bought fashion online92.4%
Ordered groceries online91.6%
Subscribed / renewed OTT86.6%
Booked movie or event tickets79.0%
Bought electronics online78.2%
Booked travel tickets75.6%
Booked a service (Urban Company etc.)71.4%
Booked a hotel / holiday stay69.7%
Attended an online course37.0%
How to caveat this study. n=119 against a target of 100, metros only, NCCS A/B only, 99% aged 25–44, and every respondent has consulted a doctor in the last 6 months. Cohort cells (30–52) are below the workbook's own 60-respondent threshold for confident reading. The findings are a strong directional signal for a metro, affluent, digitally fluent audience — not a projectable national estimate.