Page 1 of 1

How to do this?

Posted: Tue Jan 07, 2025 6:44 am
by sadiksojib35
First, you need to understand whether it is worth putting up or extending the promotion at all. Such an analysis should be done before and after each campaign. Moreover, as described above, if you are guided by only sales growth and do not take into account other effects, you can mistakenly hold an unprofitable promotion.
If the campaign is still effective in retrospect, you need namibia whatsapp phone number to answer the questions: how long and how often should you run the promo in the future? If the campaign lasts for a very long time or is constantly repeated - is this a sure sign of a "promo needle"? How to avoid getting caught in it?

There are three options.



Place promos dedicated to certain events
The promotion can be tied to such events as New Year, March 8, September 1, the European Football Championship and others. In this case, the duration, frequency, and range of the campaign (which products are included in the promotion) will depend on these events.

Typically, promotions last for some time before and after the event, and the assortment is timed to coincide with the event (for example, a promotion on stationery before September 1).



Conduct test&learn — independently generate data for advanced analytics
In this case, analytics will already indicate the optimal duration and frequency of the promotion. This approach to promotion is smarter. It allows you to rotate the frequency and range of campaigns depending on their historical effectiveness.

For this purpose, promotional campaigns are tested. For example, we made a discount on a product for one week and looked at how it affected sales and other components that we described (halo, cannibalization, etc.). Then the same campaign can be set for two weeks, then take a break for a week, launch again or in combination with other products and see algorithmically which of these combinations is the best in terms of the combined effect of all the components considered earlier.

This approach works mainly in categories with a quick response and frequent purchases, such as dairy products. Otherwise, you may not have time to accumulate enough data for analysis.