Title: Behavioural Targeting
Author: Kriko
Published: Feb 13, 2021
Last modified: Jul 14, 2026

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# Behavioural Targeting

**Behavioural targeting** is a digital marketing method that uses signals from users'
behaviour across websites, mobile applications, search engines, social media or 
other digital touchpoints to deliver more relevant ads, content or offers. This 
approach evaluates not only demographic information, but also behavioural [data](https://kriko.io/services/data-analysis-insight)
such as visited pages, viewed products, items added to cart, search behaviour, clicks,
content consumption, session frequency and user journey patterns.

The main purpose of behavioural targeting is to better understand user interests
and purchase intent in order to show more relevant messages. For example, if a user
views running shoes on an e-commerce website, compares products and leaves without
adding anything to the cart, they may later be shown ads for running shoes, sportswear
or related campaigns. This structure allows users to receive more personalized and
contextually relevant communication instead of broad, generic advertising.

In this method, user behaviour can be analysed through different [data](https://kriko.io/services/data-analysis-insight)
sources. Web analytics tools, advertising pixels, cookies, mobile app SDKs, CRM 
[data](https://kriko.io/services/data-analysis-insight), email interactions, product
view history and purchase behaviour are among the [data](https://kriko.io/services/data-analysis-insight)
sources that can be used for behavioural targeting. However, the collection, processing
and use of this [data](https://kriko.io/services/data-analysis-insight) for advertising
purposes must be carefully managed in terms of legal basis, transparency, consent
and [data](https://kriko.io/services/data-analysis-insight) security.

Behavioural targeting can help brands use media budgets more efficiently. Instead
of spending the entire advertising budget on broad and irrelevant audiences, campaigns
can focus on users who show specific behavioural signals. For example, users who
previously viewed products, visited a pricing page, abandoned a form or added items
to the cart may be closer to conversion. For this reason, behavioural targeting 
is frequently used in remarketing, cross-sell, up-sell, abandoned cart communication
and personalized campaigns.

However, behavioural targeting does not always guarantee sales. A user's past behaviour
does not necessarily mean that they will purchase in the future. Misinterpreted 
behaviour can also result in irrelevant ads being shown to users. For example, someone
may have viewed baby products only to buy a gift, or may have researched an industry
product for professional reasons. Therefore, behavioural segments should be built
on data-based and regularly tested rules rather than broad assumptions.

Demographic predictions can also be made through behavioural targeting, but these
predictions should be used carefully. A user visiting sports, betting or automotive
websites does not necessarily mean that the user is male. Similarly, not everyone
searching for travel is immediately ready to buy a holiday package. Such assumptions
can lead to inaccurate, reductive or discriminatory outcomes. For this reason, modern
marketing should evaluate behavioural clusters, intent signals and user context 
together instead of relying on single assumptions.

Behavioural targeting is widely used in e-commerce. Showing relevant products again
to users who viewed them, reminding users who added items to the cart but did not
purchase, offering category-based campaigns to users who frequently visit certain
categories or recommending complementary products to previous customers are examples
of this method. When planned correctly, these practices can improve user experience
and increase conversion rates.

Behavioural targeting is not limited to ad delivery. Website personalization, email
marketing, mobile notifications, product recommendation engines, content recommendations
and CRM segmentation can also be part of behavioural targeting. For example, if 
a user repeatedly browses a specific product category, highlighting that category
on the homepage or showing related campaigns in an email can be considered behavioural
personalization.

For this method to be effective, proper segmentation is required. Instead of placing
all website visitors into one remarketing list, it is healthier to segment users
based on their behaviour. Product viewers, cart adders, checkout starters, buyers,
potential repeat buyers, inactive customers and high-value customers can be evaluated
as different segments. Instead of showing the same message to every segment, the
offer and content should match the user's stage in the journey.

Frequency management is also critical in behavioural targeting. Showing the same
ad too often can damage brand perception and create ad fatigue. For this reason,
frequency caps, time windows, campaign exclusions and exclusion of converted users
should be configured correctly. For example, continuing to show the same product
ad to a user who has already purchased it can cause both budget waste and poor user
experience.

When measuring behavioural targeting, looking only at click-through rate or impressions
is not enough. Conversion rate, CPA, ROAS, cart completion rate, repeat purchase
rate, revenue per user, assisted conversions, segment-based performance and ad frequency
should be analysed together. A/B tests, control groups and incrementality tests 
can also be used to understand whether behavioural targeting truly creates additional
value.

The most sensitive aspect of this method is privacy and [data](https://kriko.io/services/data-analysis-insight)
protection. In Türkiye, under KVKK-related decisions and guidance, cookies used 
for advertising, marketing and performance purposes are subject to explicit consent.
The KVKK cookie practices guide also states that cookies used for behavioural advertising
require explicit consent. Therefore, when user behaviour is tracked for advertising
purposes, consent processes should be clear, understandable, freely given and revocable.

In behavioural targeting processes involving personal [data](https://kriko.io/services/data-analysis-insight),
[data](https://kriko.io/services/data-analysis-insight) minimization, purpose limitation,
retention periods, security and user rights should be taken into account. More [data](https://kriko.io/services/data-analysis-insight)
than necessary should not be collected, the purpose of processing should be clearly
explained and users should be given the ability to manage their preferences. Extra
care is required in areas such as healthcare, finance, children's content or areas
that may involve sensitive data. Even if targeting provides marketing value, practices
that harm user privacy can damage brand trust in the long term.

In summary, **behavioural targeting** is a powerful marketing method that uses signals
from users' digital behaviour to deliver more relevant ads, content and offers. 
When used correctly, it can improve advertising budget efficiency, personalize user
experience and increase conversion rates. However, successful implementation requires
more than collecting data; proper segmentation, frequency control, measurement, 
consent management, data security and user privacy should be handled together.

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