Introduction
Most sellers make eye-to-eye decisions, no texting -- cutting the price, rewriting the text, putting new photos, changing the title, and then re-cutting the object, and you can't really figure out what worked.
Testing is the opposite approach, and it means not random editing, but consistent hypothesis testing. Avito's recent material explicitly describes the A/B test as comparing two variants of a single ad element to see which one is better at influencing performance, and it also lists the typical test subjects: cover, title, price, offer and how to interact with the customer.
This is especially important for plots, because land is rarely sold automatically, and its supply almost always needs market scrutiny.
What is the Testing of Advertising in Practice
Testing is about checking which variant of a particular ad element produces the best result, and it's not about comparing the whole ad at once, but about one changed item.
For a land seller, that means you can't change the first photo, the title, the price and the text at the same time, and then you can infer what actually worked. The real test answers a specific question, like, is it better to enter through water or through a glamping format, it's better to pull a header with a location or with a use.
Why Testing is More Important Than It Seems
Avito is an environment where even small changes can significantly affect the behavior of the audience. Workspace directly writes that the algorithms of the site respond to the actions of users, and the more often an ad is opened and the more often it is written to the seller, the more active it can be shown in the results.
It means that sometimes you don't have a bad site, but you just have a bad entry. The wrong first photo can kill the opening. The weak headline is not to click. The fuzzy offer is to not get to the message.
The biggest mistake in testing: change everything at once
This is the most common mistake. The seller sees a weak result and changes five things at once. If the response grows, he doesn't know what exactly helped. If he falls, much less if he falls.
The normal A/B approach is that you test one change at a time, and that's the only way you can get a controlled output.
What to Test First and First
In practice, there are five main testing areas.
The first photo or cover. Workspace explicitly names the cover as one of the key objects for the A/B test.
Title. This is another basic element to be tested, and for sites, it could be the difference between water entry, location, usage format, or investment sense.
Price or how it's presented. Price is also a typical A/B test, but it needs to be tested carefully.
Offer, which is the main point of the pitch: family, investment, tourist scenario, long horizon, low entrance.
How to interact with the client. Which leads to conversion is to call right away, send a card, send a dopphoto or first clarify the task through correspondence.
How to Test Headlines Properly
The title is one of the safest test objects if you change it meaningfully, and it often makes sense for the land to test different logs of entry: water, species, use case, location, investment sense.
The key is not to turn the test into a stream of takes. You can't multiply the same object with almost the same cards. Avito's recent material separately highlights that similar cards and massposting impair efficiency.
How to test the first photo
This is one of the strongest levers in the plots, and one might be water, another might be a panorama, and the third might be a more intuitive shot of the site itself.
The point of the test is not to choose the “most beautiful picture”, but to understand which input best matches the query of the audience.
How to Test Price Without Self-Destruction
Price is a powerful test element, but the most dangerous. Sharp and chaotic price spikes can work against an ad.
So you can test the price, but not in the neural response mode, and you need small, meaningful steps and a clear hypothesis: what exactly are you testing, whether it's an increase in the quality of the appeals, an increase in discoveries, or a change in the type of demand?
How to test the offer, not just text
Very often, the seller thinks that he is testing the text, when in fact he should test the offer – the main meaning of the ad.
The same site can be presented as a place under the house, as a point for glamping, as an investment for a long horizon or as an accessible entrance to a strong natural location. Workspace in the material about A/B tests directly singles out the offer as a separate object of testing.
How to understand what to consider the result of the test
Looking at views is a mistake. It's not enough for the ground. The test can give more discoveries, but the quality of the messages is worse. Or less discoveries, but more accurate demand.
Therefore, the result should be evaluated by the funnel: opening an ad, messages, quality of dialogue, transition to a call or viewing.
How long to test?
You can't stop the test too early. You need enough data to draw conclusions. The general A/B test material says that you have to do it until you have enough information to draw conclusions.
This is especially important for land because the demand here is not as massive as in other categories.
How to test if there are many objects
When you have multiple sites, testing becomes even more important, but the risk of chaos increases, because you can't test everything on all sites at once.
You have to identify the typical groups: waterside, species, long-range agricultural land, glamping areas, and then within the group, check which input works best.
Practical conclusion
Testing adverts for the sale of a site on Avito is not a stream of experimentation for the sake of experimentation; it's a way of figuring out which input really works on your type of object: a photo, a headline, a price, an offer, or a way of putting it into contact. Avito's latest materials confirm two pillars of this work: changing one element at a time and looking at real behavioral metrics.
The big takeaway of the fourteenth lecture is that the strong pitch of the site is not inspiration, it's disciplined testing. One object. One question. One change. One clear conclusion.
Questions and answers
Do I need to test several elements of the ad?
No. The normal A/B approach involves changing one element at a time.
What is the best thing to test first at the site?
Most often the first photo, title and main offer.
Can I test it with a few similar ads?
It's bad practice. Similar cards and takes create problems.
Do I need to test the price?
Yeah, but be careful, jumps are bad.
When can I conclude the result of the test?
When there is enough data on user behavior.
