Targeting: The key to effective marketing
7min • Last updated on May 26, 2025
Olivier Renard
Content & SEO Manager
We’ve all experienced poor targeting.
Are you vegetarian? Yet you receive promotional emails for minced beef.
Subscribed to your favourite gym? You’re sent “new member” offers.
A B2B SaaS software provider? “Discover our best parcel delivery solutions.” 👀
These situations might seem amusing, but they often irritate customers and can be costly for brands.
Key Takeaways:
Targeting in marketing means selecting the customer segments you want to focus on.
It relies on good segmentation and clear criteria: needs, potential, and accessibility.
Effective targeting improves campaign performance and avoids wasted effort.
First-party data and Customer Data Platforms (CDPs) enhance your campaigns by delivering the right message, at the right time, to the right audience.
👉 Learn what marketing targeting is, explore its different forms and stages. Understand how to define your audience and activate the right levers to improve campaign efficiency. 🎯
What is targeting?
Targeting in marketing is the process of identifying and selecting the most relevant customer or prospect segments for a specific campaign or offer.
Rather than trying to reach everyone, a company focuses its efforts on the audiences most likely to respond positively to its message.
This is a crucial step in building a marketing or sales strategy. It allows companies to:
Personalise their marketing actions (what content, through which channel, at what time?)
Avoid unnecessary spend, energy loss and diluted efforts
And increase campaign ROI (return on investment).
Defining your target is no longer just about generic criteria like age, gender or location. It now involves behavioural, transactional or CRM data to create more refined segments and tailor messages in real time.
Two concepts, one objective
Customer segmentation and targeting are often confused, yet they are actually two distinct steps:
Segmenting means analysing your audience and dividing the market into homogeneous groups based on specific criteria (profile, behaviour, purchase history, etc.).
Targeting is a strategic decision: selecting which segment to prioritise based on marketing objectives, budget, or commercial potential.
Segmenting is about understanding, targeting is about taking action.
Segmentation vs Targeting
Segment well to target better
The STP model
The STP model (Segmentation – Targeting – Positioning) was popularised by Philip Kotler in the late 1960s. It’s a straightforward framework built around three distinct phases:
Segmentation involves analysing the market, audience, or customer base to identify groups that share common characteristics.
Targeting is about selecting the most relevant segments to address.
Positioning aims to define a communication strategy tailored to each target.
💡 A clothing brand might, for example, segment its audience by age and lifestyle (e.g. young urban professionals vs active retirees). It chooses to target only the first group, and adapts its message accordingly (e.g. “Urban style, delivered in 24 hours”).
The STP model helps make sense of complex markets, identify growth opportunities, and align both product offering and messaging with real customer expectations.
It’s also an effective way to optimise resources, avoiding overly broad or inefficient campaigns.
What are the main segmentation methods?
There are several ways to segment an audience, ranging from basic to advanced techniques. The right approach depends on the data available and the objectives you’re aiming to achieve.
Traditional criteria
Socio-demographic: age, gender, income, socio-professional category.
Geographic: country, city, climate, catchment area.
Behavioural: purchase frequency, preferred channel, product usage.
Advanced approaches
RFM segmentation: based on recency, frequency, and monetary value of purchases.
Customer scoring: using internal models or machine learning.
ABC matrix: combines frequency and volume of purchases to classify customers based on their contribution to revenue.
LTV-based segmentation: identifies the most profitable long-term customers to better allocate marketing investment.
Purchase intent: inferred from user behaviour (clicks, browsing, weak signals).
AI-based segmentation: built from behavioural similarity or activity clusters.
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Mettre en place votre segmentation RFM
Various tools can help refine segmentation depending on your needs. A CRM helps leverage historical customer data, while web analytics or product analytics tools are used to analyse online behaviour.
Finally, a Customer Data Platform (CDP) unifies and enriches data, making it easier to activate segments across multiple channels.
⚠️ Beware the pitfalls of over-segmentation: Excessive segmentation can reduce overall effectiveness. Creating 20 micro-groups with little strategic impact may undermine the clarity and impact of your campaigns. On the other hand, overly broad segments make personalisation impossible.
How to succeed in your targeting
Effective targeting is based on clear criteria and a structured process. It must be relevant, achievable, and aligned with the company’s overall objectives.
Key criteria for defining your target audience
Segment size: as mentioned earlier, it must be large enough to justify a dedicated campaign but not so broad that precision is lost.
Economic potential: the target should represent a measurable opportunity in terms of revenue or growth.
Accessibility: you need to be able to qualify the audience using available data and reach them through the right channels (email, social media, SMS, app, etc.).
Compliance: all targeting initiatives must respect applicable regulations (GDPR, consent, opt-in).
Brand alignment: the selected target should be consistent with your brand values and positioning.
Steps to successful targeting
1️⃣ Understand your offer and objectives
Identify what you want to promote, why, and with what expected outcomes (sales, sign-ups, awareness, etc.).
2️⃣ Select the most relevant segments
Segmentation is the foundation of targeting. You then cross-reference it with potential, accessibility, and profitability criteria.
3️⃣ Adapt the message, channel, and timing
Each target requires a tailored message, format, and moment to maximise impact.
4️⃣ Test, adjust, iterate
Targeting isn’t improvised. It must be tested, measured, and refined based on performance.
Different targeting strategies
There are several types of targeting approaches, depending on the chosen strategy and available resources.
Type of targeting | Principle | Benefits | Limitations |
|---|---|---|---|
Undifferentiated (mass marketing) | One single offer and message for the entire market. | Easy to implement. Economies of scale in campaigns. Suitable for mass-market products. | Low level of personalisation. Message may not resonate with all profiles. Less suited to high-end products. |
Multi-segment | Several segments are targeted, with tailored offers and messages for each. | More precise targeting. Better message relevance. Works well with diverse audiences. | More complex to manage. Higher marketing costs. Requires reliable data. |
Concentrated (niche targeting) | Focuses all efforts on a single segment identified as strategic or high-potential. | Highly focused strategy. Message perfectly tailored. Strong potential for differentiation. | Smaller market. Requires very well-defined audience. Risk of over-dependence on a single segment. |
Different targeting strategies
The choice of strategy depends on the company’s positioning, the diversity of its customer segments, and its ability to personalise campaigns. Whatever the approach, it must be based on reliable, actionable data.
Targeting in the age of data-driven marketing
In an omnichannel environment, customers interact with your brand across multiple touchpoints. This means you need to rely on complete, unified data to build a 360-degree customer view.
The data warehouse plays the role of a single source of truth. It consolidates information from various sources (CRM, website, app, support, etc.) into a scalable environment designed for analysis.
The composable CDP builds on the centralised data in the warehouse to launch campaigns targeting specific segments. Easy to implement, it enables the rapid deployment of high-value use cases. For example:
Automatically exclude inactive customers (or churners) from a campaign to avoid wasting budget, and plan a reactivation campaign alongside it
Activate segments based on predicted LTV, to focus efforts on your most profitable customers
Adapt the message based on the customer’s channel or recent behaviour (visit, click, purchase, etc.)
Thanks to this modern data infrastructure, targeting becomes faster and more precise. It can be managed entirely by marketing teams, reducing reliance on technical or data teams.
How the DinMo composable CDP works
How can you continue to target effectively online?
Browser restrictions, widespread use of adblockers, refusal of consent, and the gradual disappearance of third-party cookies have all disrupted traditional practices. Techniques such as behaviour-based retargeting are now being challenged.
In response, brands must rethink their approach. The alternative? Rely on first-party data, the data they collect directly through their own channels: website, CRM, mobile app, customer service, and more.
When centralised in a data warehouse and activated through a CDP, this proprietary data offers several key advantages. It enables compliance with privacy regulations like GDPR, while supporting more accurate and relevant segmentation.
It also opens the door to AI-powered activation scenarios, based on predictive models. And above all, it empowers operational teams to take control and act autonomously.
Conclusion
Targeting remains one of the most powerful levers for optimising marketing campaigns and improving overall performance. To be effective, it must rely on well-defined segments and trustworthy data.
In a landscape shaped by the end of third-party cookies and the rise of first-party data, composable CDPs offer a tailored solution. Targeting becomes more precise, faster, and better aligned with the needs of operational teams.
👉 Want to go further? Discover how DinMo’s composable CDP helps you activate your audiences directly from your data warehouse — with no technical skills required.
FAQ
How to measure the effectiveness of targeting?
How to measure the effectiveness of targeting?
The effectiveness of marketing targeting is assessed using several key indicators: conversion rate, cost per acquisition (CPA), and return on investment (ROI) of the campaign.
Good targeting also helps reduce unnecessary spend and improve message relevance.
Analysing performance by segment, or through A/B testing, helps confirm that the right audiences were selected and properly activated across the right channels.
Is targeting just as relevant in B2B as in B2C?
Is targeting just as relevant in B2B as in B2C?
Yes, targeting is just as essential in B2B, even though the logic differs. In B2C, targeting often involves large volumes and is based on behavioural or socio-demographic criteria.
In B2B, targeting relies more on factors such as company size, industry sector, or the decision-maker’s role. The buying cycle is generally longer.
In both cases, a modern, data-driven approach enables better segmentation, target prioritisation, and large-scale personalisation.
