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Bootcamp update 29th March Q3 FY 23

Q3 performance

CM stands at $1.9M from $1.2M from previous runs

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Q3 Paid channels

CM increase has been majorly driven by paid channel ($400K up).Paid uplift has come from Google.

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Q3- social

On social we have tried to control the -ve CM

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Channel distribution

Reduced school contribution from 16% to 12% in PAs. Other paid has improved because of more remarketing campaigns. Email has improved with more reactivation emails being sent.

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Key initiatives

Remarketing and RLSA

Quarterly Data:

375% increase in PA’s in FY23-Q3 when compared with previous quarter from remarketing campaigns.

In Bootcamps, We've spent close to 40K for remarketing campaigns and our CAC from these campaigns are at 32.5%

Although, CPC’s have increased, improvements in CTR, L2PA can be seen.

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Courses that performed:

MO-PCCY - Spent extensively for remarketing

5 PA’s at a decent CAC of 43%

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MO-PCCO -

5 PA’s at a good CAC of 31%

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IMP-PCMLAI - Need to scale and spend more

So far, 3 PA’s at a great CAC of 17.8%

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MO-PCTPM - Falls under Q4 data.

CAC is good but need to scale and spend more

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Course wise performance

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IMP-PCMLAI-23-03

Currently seeing its best run ever;

Running CM at $102K, 104% better than previous best.

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- Optimized spending on Google by pausing irrelevant keywords (headterms), and directing higher spends (+10%) towards better converting regions (UK).

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- Saved ($10k-$12k) by not running Facebook which historically has a very poor CAC.

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- Improved contribution from Non-paid channels (primarily school- avg 5 vs 13 and direct Avg 2 v/s 11)

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KLG-PCDM

Overall performance

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Best performance from Google ads in this run when compared with the previous runs.

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CAC for paid channels also declined to 31%.

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Best CM from Google ads compared to previous runs.

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Changes Made:

In past runs, head terms campaigns (mostly phrase) used to have a high spend share of close to 15% with a negative CM. In this run, we lowered its spend share to 2%, with CM in the positive range.

Previous run:

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Current run:

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Targeting outside of US:

In January run, we spent 23K outside of the US and CAC was over 350%. This run we lowered spends and targeted only a few countries outside the US. CAC was at 98%.

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Bing:

Experimented on Bing at a minimal budget. We managed 2 PA at a CAC of 3.1%.

Brand: 1 PA

Non Brand: 1 PA

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Other Paid:

Two paid apps from sub channel: gg_other_nonbrand which helped in gaining 12.48K additional revenue. Not able to attribute it to a particular campaign, it’s a catchall bucket. Analytics is working to fix it.

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Summary:

Spends lowered from over 100K to 66K

However, PA’s this time is better at 51 vs 43 in last run

Eliminating Head terms campaign and majorly focusing on US Helped improve CAC efficiency.

Next Up:

Canada gave us 2 PA’s. Our WW campaigns targeting should be more focused on countries that convert.

Not running Head Terms campaign from start. Use it when need to scale lead volume.

Continue running on Bing to see if it works in the long run.

MO-PCCY:

Overall Performance:

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Google + Other Paid:

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RSLA Experiment:

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Wins:

Better Non-paid and Paid channel performance in March run.

Google performed better than Jan run in terms of PAs and CM contribution. Saw a growth of 1325% in CM RoR.

Remarketing (RLSA) experiment worked well for PCCY. - Generated 5 PAs at a CAC of 33% and this resulted in getting an additional CM of $11K.

Initiatives:

Corrective and Judicious spending: Restructured the ad groups and clubbed the keywords basis their past performance. This helped in spending less on low performing keywords. Judicious scaling of the campaigns also helped in controlling the overall NonBrand spends.

Activating TCPA bid strategy for Brand campaign: TCPA Brand campaigns gave better CTR, Conversion rate and Cost/Conversion and this ultimately helped in spending less on the brand campaign for the same number of leads, helping in improving the Brand CM.

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MO-PCDE:

Overall performance:

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Much better performance in March run than the Jan run.

Same days out we are at $133k Vs $68k (95% increase in RoR CM)

The performance of both Paid and Non-paid channels contributed well together in march run and thats the main reason we can see a major spike in the CM run over run.

Non-Paid Performance:

PAs from Non-paid channels increased from 11 to 20 in March run.

CM increased from $48k to $77k in march run.

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MO-PCTPM:

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Remarketing Campaign performance:

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Wins:

Remarketing campaign (RLSA) helped in generating additional revenue of $14k for the course and added positively (+$6k) to the overall course CM.

NYUT-PCXR-23-03

Overall CM at all time high of 63K in this run. We started this run with 10 deferred PA’s.

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CM from Google ads as well has improved to 24K.

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Misses:

We started a new campaign based on good performing keywords from NYUT-ARVR and had good search volume. Although, the campaign had 20 leads at $118 CPL, there were no PA’s.

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Unity campaign was the best performer among all non brand campaigns in previous runs. This run its performance has declined.

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Non paid channels have performed better this run

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Next Steps:

Optimize unity campaign.

Take a call on running unitynew campaign which had 20 leads but no PA’s.

Try to scale brand campaign further.

BH-PCMLAI-23-02 closes with best ever - - gross CAC at 21.8% — which is 43% lesser compared to the previous best, with similar gross PAs (87 vs 89) - CM $89K vs previous best $37K

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How? - Campaign restructuring on Google by clubbing multiple ‘similar’ adgroups into a single adgroup for better spend optimization - Bidding only on high intent ‘Exact match’ keywords instead of Phrase & Broad match

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- Lesser spend on Social which is a high CAC channel here

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- Improved conversion rate and contribution from non-paid channels (no significant outlier. Increase across all non paid channels)

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New Programs

MO-PCDS-23-02 first run closed with 15 Gross Paid Apps @48.3% CAC. A positive CM achieved in the 1st run

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How? - High intent Phrase & Exact match keywords targeted on Google - No spends on Broad match keywords - No spends on Social (Facebook) in the 1st run (Program name change experiment was underway during the marketing cycle)

MO-PCGD-23-02 - Originally scheduled to launch in Q2, the program was struggling with 3 PAs @258% CAC at a spend of $47K. - Run postponed and closed in Q3 with 14 Gross PAs @85% CAC at a spend of $68K i.e. 11 additional PAs with a spend of $21K - translating to a 30% CAC How? - Switched from Broad match keywords to Phrase & Exact match on Google - -ve keyword addition to stop bidding on irrelevant search terms - Cut-down spends on Facebook early in the run when no traction was seen on MDRs

Misses

MO-PCCO-23-02

Single keyword adgroup structure was tested for MO-PCCO-23-02 in an attempt to scale leadgen from highest volume keywords.

Although we saw some improvement in our Imp. share and Top imp. share, at the campaign level the CPCs rose significantly leading to higher cost/conv.

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With the new single keyword structure, the exact match keyword saw v. high CPCs and poor conversion rates, resulting in high CPLs.

CPLs for the phrase adgroup also are seen trending higher compared to the old campaign structure (avg CPL $180-$200).

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KLG-PCPM-23-03

- Although the CAC was maintained, we saw a drop in paid apps compared to earlier runs

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- This drop was primarily observed from the ‘School’ channel, amongst others

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- Other channels saw marginal drops of 2-3 Paid apps each.

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Bootcamp update 29th March Q3 FY 23

Q3 performance

Channel distribution

Remarketing and RLSA

Course wise performance

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MO-PCCO-23-02

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