The interaction of the user with the product, strongly exaggerating, can be divided into three stages-cases: before, after and instead of. User searches in all variants affect a product or service in one way or another. But interaction with them may not be interesting to us.
How to identify where the user is at? Preparing, looking for alternatives, or have you already bought and used?
The classic approach in contextual advertising and SEO involves a detailed manual elaboration of the semantic core with human judgment. We need to determine which search query is relevant and which is irrelevant to our proposal.
In my time, I found that a quick way to spot this is to identify markers that will identify each of these cases and find a way to quickly mark all such searches. But there is another way – you need to go from the opposite: do not identify queries in the already assembled huge semantic core (as a rule, in most projects it is large), but identify non-target queries first.
I share my best practices. The list of markers is not final and is not always accurate for any business, but in general it will be very useful in most topics.
So, stages and markers.
This includes many queries related to people’s fears, doubts and the desire to dispel them by turning to search. This is a warm audience. As a rule, it does not have a high conversion rate, but with skillful work it can be profitable, since often they prefer not to bother with it and leave it for later by your competitors. Marker words:
- review / video feedback
- review / video review
- whether (is it painful, is it harmful, is it worth it, is it necessary, is it possible, is it possible, is it good, is it really …)
- before + service – in the service sector
- before + purchase + goods – in the field of commodity sales
- which + all word forms before the name of the product / service
- good + all word forms (best, better)
- most + all word forms
- rating / top
- harm + all word forms
- if a
- v / v + service / product
- with + service – in the service sector
- before + service – in the service sector
This includes search queries that identify problems that the user has after purchasing a product or service. This may be any defects in a poor-quality product or the consequences of a poor-quality service, the need to replace, return or repair a product, or search for consulting material – what to do and how to act in new realities. Basic markers:
- for + product (parent case)
- under / under + product (wine case)
- for + product (except purchase markers: product price, product discounts)
- w / w + goods (wine case)
- to / to + product (creative case)
- from + product (parent.case)
- commodity + not
- product + verb (except for purchase marker verbs)
- as (in product semantics, except for phrases with purchase markers)
- after + services (childbirth) – in the service sector
There are a lot of markers of negative consequences, other damage and ways to eliminate it, and as a rule, they are specific for each topic, especially for the service sector. However, some are open source and can be downloaded and used.
Stage “instead of”
Everything is simple here: the user is either not our potential client at all, or the probability of this is about zero. He is looking for an alternative to our service or product, and not necessarily a paid one. There are a lot of similar interests and activities, user portraits can be completely different, for example:
- student or specialist – looking for articles, abstracts, coursework, courses, educational institutions, etc .;
- DIY enthusiast – looking for manuals and instructions, trying to do everything with his own hands;
- porn lover;
- seeker of meaning (dream books, horoscopes, omens, prayers, fortune telling, love spells, etc.);
- an inveterate onliner (echoes some of the above) – looking for anecdotes, jokes, vidyahs, drovishki, software, desktop wallpapers and other similar things.
All of these comrades can mention your product or service, but only within the framework of their topic.
It will be useless to list markers within the framework of this article, there are many different markers on the Internet, and in my free Excel file with the code name “Recognizer Robot”, it will not be difficult to find it.
Well, we got acquainted with various user portraits at different stages of their customer journey and in other cases. I think many have guessed what to do with all this – to compile large lists of negative keywords based on these queries and cut off irrelevant audiences.
My main helpers in this are Yandex Wordstat, Yandex search hints, keyword databases and the fruit of my hobby, which is using VBA to analyze semantics – an add-on! SEMTools. I will describe my algorithm in detail at SEMconf.
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