User Intent: Enhancing the Digital Campaign with User Factors

Original author: Chandal Nolasco da Silva
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We thank our readers for their attention to our publication yesterday on behavioral factors and their analysis by the search engine itself. Your votes are important to us as an assessment of our work and feedback is important to us. Thanks! Today, let's look at the same behavioral factors from the opposite side: how can a marketer conduct research and plan the creation of more prosperous sites using data on behavioral factors? The author talks about the concept of "Person" and refers us to a number of publications describing algorithms for working with PF for a marketer. At the end of the article, we suggest you select the next article that you would like to see in our blog in translation. As always, thank the ALTWeb Group analytics department and the SERPClick teamfor help with the translation.

Effective digital platforms are making efforts to control user behavior and get the desired return from it. In this they are helped by data on user behavior. This data, in turn, allows you to improve the site with adaptive changes that will attract even more users.

User factors, of course, are directly related to the user's intention. You can understand what type of person your client is through the prism of his actions: this data will allow you to predict the route that your client will most likely route through your website.

Experts both in the field of optimization and in the field of digital campaigns are familiar with the opportunity to find out the user's intention, based on data from search marketing. They try to anticipate and classify the intentions that indirectly derive from the keywords by typing which the user entered the site. Thus, the specialist can find more more accurate keywords that will lead users who convert to leads and sales. However, while user intention and search go hand in hand, search traffic specialists need to take a closer look at the intention if we all want to get the most out of our campaigns.

Behavioral factors

“Persona” was a buzzword for a long time (in foreign marketing, not with us - approx. Translation), when it came to determining the intent of the user.

The word refers to a certain type of person or group of people who share important common features. By grouping cohorts of people with similar attributes, we can begin to set certain patterns and become a little closer to the ability to predict consumer and other types of intentions. Then, we can position products for certain groups of customers in a more targeted manner.

Classification and segmentation of users is an extremely useful and important type of activity for search marketers. For example, it is important to consider that the wider the search query, the less intention is to buy something from the user who came through it. A shoe seller may have to decide whether or not he needs the keyword “shoes”. From a brand or traffic perspective, this is a potentially useful keyword. However, short keywords of this type are usually not only expensive, but also do not represent an intention to buy. On the contrary, a user who came by a short keyword is engaged in research and information search.

In this case, the intention to buy would be higher when using the keyword “knee-high military boots with buckles and buckles”. In this case, the chances that a person is looking for them to buy are really high. Jason Hawkins talks more about user portraits or persons in this SEMrush post (which, most likely, we will translate for you later - approx. Transl.). In his post, he emphasizes that users who collect information compare products - and first of all, it is important to note that they compare products that they want to buy.

Data Tools

The basic commandments for defining a user’s portrait were discussed in sufficient detail in the article “ Portraits of users in search: how to work with optimization aimed at the user», Which appeared in Search Engine Watch (in English - approx. Transl.) I highly recommend this article for those who would like to improve their work on optimization, to investigate users' intentions. At the end of the article, it is mentioned that data collection is the most difficult. The data is indeed the fundamental tool for the optimizer and the marketer, but to collect it in the era of “Not Provided” (the term “not indicated” - a term for a milestone in marketing when Google refused to provide search queries for the site directly to GA and the ensuing difficulties for optimizers - approx. transl.) However, do we have the opportunity to explore user behavior somehow else and enrich our search strategy?
Keyword Not Provided
Matthew Butler, Ph.D., who works at iPerceptions, expressed this opinion in a recent press release : “Two fundamental problems in collecting data when researching user behavior are collecting accurate data and being able to respond [to changes in user behavior] in real time” . Matthew leads the team that developed the Internet Recognition System, which solves the problem of creating a personal user environment in real time. According to him, this solution uses "15 million standardized units of user data."

In one of his last postsAvinash Kaushik speaks in sufficient detail about how to get the most out of using the data to which we can have access. In addition to the traditional optimizer tools, it offers a method of working with keywords with a more efficient use of the Google Webmaster Tools tool, the Google Keyword Planner, as well as the Google Trend tool. It is interesting to note that at the end of his post he considers the future possibilities of tools for analysis and describes a tool for “Personal Page Analysis”, which he apparently gave the name to. In his case, the user's identity that the page should reflect comes to the fore.

When User Segmentationwas added to GA last year as one of the features of the system, we were able to see various user personalities or behaviors in our target audience. And then it became clear: effective analysis and marketing are movements towards a personalized user experience.

Persons, cohorts and user segmentation are just what we need for this. The same person can be described by different Persons, and the intent of these persons will vary depending on the circumstances. Someone may behave in a certain way on your site on their day off, while the next day the behavior will change for any arbitrary reason, for example, because he or she is late for school to pick up children in the evening. The most effective campaigns will operate not only with one Person, trying to bring the content closer to the needs of a living person in real conditions.

What conclusions can be drawn for search engine optimizers?

While the tools for working with keywords still remain very useful in order to create new useful pages and generate natural search traffic to them, we still do not know the exact laws between the search query and user behavior. However, if we pay more attention to analyzing user behavior, we can not only create responsive web pages that satisfy the user's intent in the form that we were able to determine, but we can also use this information to create more successful marketing strategies.

Potentially, we can expand the list of our queries and keywords and predict which particular queries will be especially useful to us, based on correctly collected data. If we can determine the relationship between the request and the type of user coming through it, we can better understand which marketing tools we need to use.

List of articles on the voting
method of analysis of search queries to increase sales and conversions, SEMrush, Jason Hawkins
user-oriented promotion, Search Engine Watch, Guillaume Bouchard
Ways to solve the problem Not Provided, Avinash Kaushik
new approach to segmenting users in GA, Tom Craver

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Which of the articles mentioned in the text interested you and would you like to see it translated?

  • 66.6% Search Query Analysis Method to Increase Conversions and Sales, SEMrush, Jason Hawkins 2
  • 0% User Oriented Promotion, Search Engine Watch, Guillaume Bouchard 0
  • 33.3% Solutions to the problem Not Provided, Avinash Kaushik 1
  • 0% A new approach to user segmentation in GA, Tom Craver 0
  • 0% You know, I want to offer you a completely different article (use a personal message, please) 0

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