Thoughts on Analysing Year On Year data | Community
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David_Jerome
David_Jerome
Level 6
April 3, 2024
Question

Thoughts on Analysing Year On Year data

  • April 3, 2024
  • 2 replies
  • 757 views

Hi there,

 

I was wondering if anyone has experience that they can advise on based on the following. As bit of background before any simple ideas are suggested:

 

I am a long-time Adobe Analytics / SQL / Tableau / Python user and was curious if anybody had thoughts on how they would approach YOY analysis for the following: Our business is in travel - but the same principle could be applied to retail to an extent - our performance is down YOY. There are many different things that could be driving it; for every quote, there are multiple locations/dates of travel/lengths of travel/number of options and, of course - price. In total, there are around 10 key dimensions/metrics, but each of these could be hiidden only showing itself when used in conjunction with something else - for example trips over 10 days in Spain. Some of these dimensions have 50+ options.

 

As you can imagine - this makes the analysis in workspace (other than a segment comparison) / tableau not possible and would need some kind of tool to analyse the data for me. Has anybody got any experience on a tool that they could recommend? We have our Adobe data in SQL if needed.

 

Thanks

 

Dave

 

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2 replies

Nick_Walter
Community Advisor and Adobe Champion
Nick_WalterCommunity Advisor and Adobe Champion
Community Advisor and Adobe Champion
April 3, 2024

Sounds like a lot of interesting data to me!
If you are using CJA I attended a good breakout during summit where they were using python and plotly to do some cluster modeling with t-SNE that I think could be useful here. You could hopefully get a new perspective on your users.
As far as other "simple" ideas that I would think to look into would be:

  • Distance - YoY how far are people willing to travel
  • Trip length - Are people taking more weekend or short trips to save money? 
  • Time to purchase - How many time are people coming back to your site and how many trips are people clicking in before choosing?
    • Are they making a decision in a day or thinking about it for a month?
  • Lead time - How far in advance are people planning and is that growing or shrinking YoY?
  • Flexibility - When a user comes in to look for a specific trip category (lets stick with the Spain trip as an example), are they firm on going to Spain or do they start looking for closer, less expensive trips?
    • If they are discouraged by the price of the trip they really wanted, could the sale be salvaged by suggesting a less expensive trip (maybe a Mediterranean curse)
    RobertBlakeley
    Community Advisor
    RobertBlakeleyCommunity Advisor
    Community Advisor
    April 3, 2024

    From time to time I have used Adobe's contribution analysis to identify key dimension contributions.

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