A comprehensive analysis of marketing performance metrics showing why accurate, segmented, campaign-ready data gives marketers a stronger foundation than one-size-fits-all lists
The gap between marketing teams that use data effectively and those relying on generic lists continues to widen. Although 64% of marketing executives strongly agree that data-driven marketing is essential, many organizations still struggle to turn available information into accurate audiences, relevant messages, and measurable campaign outcomes.
This gap creates an opportunity for marketers that invest in custom data solutions built around specific campaign objectives rather than settling for one-size-fits-all databases. Better-prepared data does not guarantee campaign success. Creative quality, offers, timing, channel selection, consent, and measurement also matter. However, incomplete, outdated, duplicated, or poorly segmented records can weaken those investments before a campaign reaches the intended audience.
Key Takeaways
- Data-driven execution remains uneven. Only 32% report strong success with their data-driven marketing strategies.
- Personalization is now expected. Seventy-one percent of consumers expect personalized interactions, while 76% become frustrated when companies fail to provide them.
- Segmentation improves engagement. Mailchimp reports 23% higher open rates and 49% higher click-through rates for segmented email campaigns.
- Data partnerships are changing. Sixty-eight percent of marketers are reevaluating third-party data partnerships.
- Large volumes of data remain unused. A Seagate and IDC study found that 68% of enterprise data was not being put to work.
- Analytics investment continues growing. The audience analytics market is estimated at $5.71 billion in 2026 and projected to reach $9.71 billion by 2031.
Data-Driven Marketing Strategy Statistics
1. 64% Strongly Support Data-Driven Marketing
Invoca reports that 64% of marketing executives strongly agree that data-driven marketing is essential in the current environment. This broad agreement shows that data is no longer treated as an optional campaign resource. It now influences audience selection, budgeting, personalization, channel planning, measurement, and customer experience. The practical challenge is ensuring the available information is accurate and usable. A large database does not automatically create better results if it contains duplicate records, outdated addresses, irrelevant prospects, or inconsistent formatting.
2. Only 32% Report Strong Success
Ascend2 found that only 32% of surveyed marketers described their data-driven strategies as very successful or best in class. This result highlights the difference between collecting data and using it effectively. Strong execution requires clear campaign goals, appropriate audience definitions, reliable records, and information formatted for the intended systems and channels.
3. 63% Report Moderate Success
Another 63% of respondents described their data-driven marketing strategies as somewhat successful. This group represents the largest improvement opportunity. Many organizations already collect substantial customer and prospect information but struggle to standardize it, connect it across systems, or translate it into precise campaign audiences.
4. 47% Find Data Useful for Email
Email was the most commonly selected area where data-driven marketing was useful, cited by 47% of respondents. Email performance depends on more than having an address. Marketers also need relevant customer attributes, current status information, proper suppressions, and audience definitions that match the campaign objective. A broad contact file may produce weak results if it includes inactive addresses, current customers receiving acquisition offers, or people outside the intended market.
5. 46% Use Data for Journey Mapping
Customer experience and journey mapping were selected by 46% of marketers. Journey analysis becomes more useful when customer records can be matched across systems and channels. Without matching and standardization, the same person may appear as several unrelated records, preventing marketers from seeing a complete sequence of interactions.
6. 90% Say First-Party Data Is Important
Think with Google reports that 90% of marketers consider first-party data important to digital marketing, but only one in three say they use it effectively. The gap shows that collecting customer information is not the same as preparing it for targeting, measurement, and activation. Marketers still need consistent identifiers, accurate records, clear consent practices, and processes that connect data across channels.
7. 14% Cite a Lack of High-Quality Data
HubSpot reports that 14% of B2B marketers identify a lack of high-quality data as one of their biggest challenges. Even when the percentage appears smaller than broader concerns such as sales and marketing alignment, poor-quality data can affect every stage of execution—from audience selection and routing to personalization and reporting.
8. Only 35% Have Fully Integrated Customer Data
HubSpot found that only 35% of CRM leaders say their customer data is fully integrated with their service tools. Although the finding comes from customer service operations, it illustrates a wider activation problem: disconnected records make it harder for marketing, sales, and service teams to recognize the same customer, coordinate outreach, and measure the complete relationship.
9. 45% Struggle With Segmented Targeting
Targeting segmented audiences was the most frequently cited challenge in Ascend2’s report, selected by 45% of marketers. This difficulty explains why purchasing a large list is rarely enough. Marketers must determine which characteristics define a qualified audience, how those attributes relate to the offer, and whether the resulting group can be reached through the intended channels. A consultative provider can help build consumer audience solutions around campaign requirements rather than asking marketers to select filters without guidance.
Consumer Personalization Statistics
10. 71% Expect Personalized Interactions
McKinsey found that 71% of consumers expect companies to provide personalized interactions. Personalization is therefore no longer viewed only as a premium feature. It has become a standard expectation across many customer relationships. Marketers cannot consistently provide relevant experiences when records are incomplete, inaccurate, disconnected, or too broadly grouped.
11. 76% Become Frustrated Without Personalization
The same McKinsey study found that 76% become frustrated when companies do not provide personalized interactions. Incorrect personalization can also create frustration. Outdated addresses, inaccurate household information, or incorrect customer status may make a message feel careless rather than helpful.
12. Faster Growers Earn 40% More From Personalization
McKinsey reports that faster-growing companies derive 40% more personalization revenue than slower-growing organizations. This does not mean personalization automatically causes a 40% increase in total company revenue. It means faster-growing companies generate a greater share of revenue from personalization activities.
13. Personalization Can Support 5% to 15% Growth
McKinsey found that personalization at scale can support 5% to 15% revenue growth in sectors such as retail, travel, entertainment, telecommunications, and financial services. This is a broad potential range rather than a guaranteed result. Performance depends on the organization’s starting point, customer relationships, execution, technology, offers, and data quality.
14. 56% May Become Repeat Buyers
Twilio Segment found that 56% of consumers said they would become repeat buyers after receiving a personalized experience. This shows why segmentation matters beyond initial acquisition. Accurate customer data can support loyalty, retention, cross-sell, renewal, and win-back campaigns.
15. 86% Say Personalization Builds Loyalty
Twilio reported that 86% of consumers say personalized experiences increase their loyalty to specific brands. Creating those experiences requires dependable customer attributes, purchase histories, lifecycle signals, and communication preferences. Personalization based on incorrect records can have the opposite effect by reducing confidence in the brand.
16. Only 18% Say Retailers Meet Their Experience Needs
Adobe’s summary of Forrester research found that only 18% of B2C consumers say retail companies meet their experience needs. The finding reinforces the difference between having customer data and using it well. Disconnected, outdated, or incomplete records can prevent brands from recognizing customers and delivering relevant experiences across channels.
17. 64% May Leave Impersonal Brands
Twilio’s 2024 research found that 64% of consumers would quit a brand if their experience were not personalized. The finding demonstrates that data quality affects more than targeting efficiency: incomplete profiles, disconnected histories, and incorrect customer status can also weaken trust, loyalty, and competitive positioning.
Email Segmentation Statistics
18. Segmentation Produces 23% Higher Opens
Mailchimp reports that segmented campaigns produce 23% higher open rates than unsegmented campaigns. Segmentation allows marketers to align subject lines, timing, offers, and content with the recipient’s interests or relationship with the organization. The figure is a platform benchmark rather than a guaranteed result for every email program.
19. Segmentation Produces 49% Higher Clicks
The same Mailchimp analysis found that segmented campaigns produce 49% higher click rates than unsegmented sends. A click requires more than attracting attention. The message must provide enough relevance or value for the recipient to take another step. Accurate audience attributes give marketers a stronger foundation for that relevance.
Data Partnership and Utilization Statistics
20. 68% Are Reevaluating Data Partnerships
Forrester found that 68% of marketers were reevaluating third-party data partnerships because of data deprecation, up from 60% in 2023. Reevaluating a partnership does not necessarily mean abandoning outside data. It means marketers must assess sourcing, accuracy, privacy, matchability, freshness, and activation readiness more carefully. Record volume alone is no longer a sufficient measure of data value.
21. 68% of Enterprise Data Goes Unused
A Seagate-commissioned study conducted by IDC found that 68% of available data was not being used by enterprises. The study surveyed 1,500 global enterprise leaders. It covered enterprise data broadly rather than marketing information alone. For marketers, the finding illustrates a common problem: collecting information is easier than cleaning, connecting, interpreting, and activating it.
22. Marketing Budgets Equal 7.7% of Revenue
Gartner’s 2026 CMO spending research reports that average marketing budgets are approximately 7.7% of company revenue. Gartner also states that budgets have remained on a plateau since 2022. When resources remain constrained, marketers have stronger incentives to reduce waste caused by duplicate contacts, unsuitable audiences, unserviceable locations, and poorly prepared campaign files.
Audience Analytics Market Statistics
23. The Market Reached $5.14 Billion in 2025
Mordor Intelligence valued the global audience analytics market at $5.14 billion in 2025. Market estimates differ among research firms because definitions and methodologies vary. This figure should remain attributed to Mordor Intelligence rather than presented as a universal total.
24. The Market Is Estimated at $5.71 Billion in 2026
The audience analytics market is estimated to reach $5.71 billion in 2026. Growing investment reflects the need to organize, understand, measure, and activate audiences across increasingly fragmented customer journeys. Technology can support those activities, but the results still depend on the accuracy and completeness of the information entering the system.
25. The Market May Reach $9.71 Billion by 2031
Mordor Intelligence projects that the audience analytics market will reach $9.71 billion by 2031. The forecast does not prove that every analytics investment will produce positive returns. It shows that organizations continue to direct resources toward audience measurement, segmentation, and targeting.
26. Audience Analytics May Grow 11.18% Annually
The same forecast estimates an 11.18% annual growth rate from 2026 through 2031. As access to analytics technology becomes more common, competitive advantage may depend less on owning another tool and more on supplying that tool with well-prepared data.
Customer Data Platform Statistics
27. The CDP Market Reached $9.72 Billion
MarketsandMarkets valued the customer data platform market at $9.72 billion in 2025. Customer data platforms help organizations organize, unify, and activate information already collected across customer touchpoints. External marketing data partners serve a different but complementary role by helping source, clean, match, enrich, and build audiences beyond the information already stored internally.
28. The CDP Market May Reach $37.11 Billion
MarketsandMarkets projects that the customer data platform market will reach $37.11 billion by 2030. The forecast reflects growing demand for more complete customer views and coordinated activation across channels. A platform can organize information, but it cannot automatically correct every missing, outdated, or inaccurate record supplied to it.
29. CDP Growth May Reach 30.7% Annually
The same MarketsandMarkets forecast estimates a 30.7% annual growth rate from 2025 through 2030. Rapid platform adoption increases the need for data governance and preparation. Feeding inconsistent or duplicated records into a central platform can spread those problems across more campaigns and customer interactions.
Artificial Intelligence and Data Readiness
30. 15.3% of Marketing Budgets Go to AI
Gartner’s 2026 CMO Spend Survey found that marketing leaders allocate an average of 15.3% of their budgets to AI initiatives. The same survey found that 70% of CMOs consider becoming an AI leader a critical goal, but only 30% report mature or fully developed AI readiness. AI can process information rapidly, but it cannot automatically turn poor-quality input into dependable output. Inaccurate customer records, inconsistent segments, and missing identifiers can weaken predictions and personalization at scale.
Why Better-Prepared Data Matters
These statistics show that marketers do not primarily suffer from a lack of information. They struggle to identify the right audiences, maintain quality, connect systems, measure outcomes, and turn available records into usable campaign inputs.
Data preparation addresses these problems before activation.
Depending on the campaign, preparation may include:
- Correcting incomplete fields
- Standardizing names and addresses
- Removing duplicate records
- Matching customer files
- Appending relevant attributes
- Suppressing unsuitable records
- Identifying serviceable locations
- Segmenting by campaign objective
- Formatting files for platforms
- Preparing multichannel audiences
These steps help teams avoid targeting outdated addresses, duplicate contacts, unsuitable households, closed businesses, or people outside the intended market.
Using First-Party and Outside Data
First-party information is valuable because it comes directly from customer relationships. However, it may contain gaps, outdated records, inconsistent formatting, or limited audience attributes.
It also includes only people or businesses that have already interacted with the organization.
Responsible outside data can help marketers:
- Correct and update records
- Add missing audience attributes
- Identify similar prospects
- Find geographic opportunities
- Build serviceable-market audiences
- Recognize mover households
- Prepare retention audiences
- Extend reach beyond customers
For example, new mover data can help brands reach households during a period when service providers, retail relationships, and purchasing habits may be changing.
Pre-move indicators may support earlier outreach when campaign timing is especially important.
How Data Quality Supports Segmentation
Segmentation divides a broad market into groups based on characteristics related to a campaign decision.
Useful characteristics may include:
- Geography
- Household composition
- Customer status
- Product ownership
- Purchase behavior
- Business industry
- Company size
- Serviceability
- Lifecycle stage
- Mover status
A segment is only useful when its defining information is accurate.
For example, a broadband campaign may begin with serviceable addresses, remove current subscribers, and then add household or mover attributes.
A retailer may need to enrich an existing customer file before identifying acquisition, retention, or cross-sell audiences.
For business audience campaigns, marketers may start with the complete business universe in a defined market before layering industry, size, location, and contact information.
Data Preparation for Multiple Channels
Email campaigns may require valid addresses, appropriate permissions, suppressions, engagement indicators, customer status, and segmentation attributes.
Data quality can reduce avoidable bounces and irrelevant sends, but inbox placement also depends on authentication, sender reputation, content, sending patterns, and recipient engagement.
Direct Mail
Every direct mail record creates printing and postage costs.
Address standardization, move updates, vacancy suppression, customer suppression, and geographic targeting can help reduce spending on records that are unlikely to produce a valid delivery or response.
Digital Advertising
Customer or prospect files may be onboarded to advertising platforms using eligible identifiers.
Matchability depends on completeness, accuracy, formatting, available identifiers, platform coverage, privacy settings, and geography.
CRM and Sales Activation
CRM data may require deduplication, company matching, account hierarchy development, contact appending, territory assignment, or lifecycle updates.
Preparing records before import can prevent duplicate accounts and inconsistent reporting.
The DataPartners Approach
Many list providers begin with a fixed database and a menu of available filters. That approach may work for straightforward requests but can become limiting when a campaign requires custom geography, multiple sources, customer matching, serviceability, suppression logic, life-event data, or specialized formatting.
DataPartners starts with objectives.
The process may include:
- Defining the campaign goal.
- Identifying the target market.
- Selecting relevant sources.
- Cleaning and matching records.
- Applying suppressions.
- Enriching missing fields.
- Creating campaign segments.
- Preparing activation files.
The result is not simply a generic list. It is a data solution designed around the intended campaign.
Building a Better Data Foundation
Start With the Campaign Goal
Before selecting data, marketers should define what the campaign needs to accomplish.
The objective may be to:
- Acquire new customers
- Retain existing customers
- Reach recent movers
- Identify serviceable households
- Find businesses in a market
- Suppress current customers
- Enrich incomplete files
- Prepare multichannel audiences
Data requirements should follow the campaign objective rather than the other way around.
Prioritize Relevance Over Volume
More records do not automatically create more opportunities.
Duplicate, outdated, ineligible, or unserviceable records increase campaign costs and distort measurement.
A smaller usable audience may be more valuable than a large generic file.
Use Appropriate Sources
No single source necessarily contains every field needed for a complex campaign.
Multiple sources may help improve coverage, add specialized information, or verify existing records. Those sources must still be matched, standardized, and deduplicated before activation.
Apply Suppressions Early
Suppressions can prevent marketers from targeting:
- Existing customers
- Recent purchasers
- Opted-out contacts
- Employees
- Converted prospects
- Ineligible locations
- Unserviceable addresses
- Other excluded records
Removing unsuitable records before activation is usually less expensive than paying to contact them.
Refresh Time-Sensitive Data
Customer status, addresses, business records, contact details, and mover information change over time.
The right update schedule depends on the audience, campaign frequency, channel, and cost of using an outdated record.
Measure by Audience
Marketers should evaluate performance by segment rather than treating the campaign as one undifferentiated group.
Useful measures may include:
- Response rate
- Conversion rate
- Cost per acquisition
- Revenue per record
- Match rate
- Deliverability
- Retention
- Incremental lift
This analysis helps determine whether a segment creates real value.
Turning Better Data Into Better Decisions
The evidence supports a clear conclusion: data-driven marketing performs best when marketers support it with accurate, usable, integrated information.
Successful teams begin with the campaign objective rather than purchasing generic lists and trying to build a strategy around the available fields.
They define the target audience based on the business goal, then prepare the data needed to reach that audience.
Raw information may require cleaning, matching, enrichment, suppression, segmentation, and formatting before it can support effective activation.
For organizations in broadband and telecom, retail marketing, business markets, or agency environments, the required sources and preparation methods may differ.
A campaign-ready approach accounts for those differences instead of applying the same list and filters to every industry.
Better marketing begins with a better audience. A better audience begins with data prepared around the campaign objective.
Frequently Asked Questions
How Does Segmentation Improve Targeting?
Segmentation separates a broad audience into groups based on relevant characteristics such as location, household attributes, lifecycle stage, customer status, business type, serviceability, or behavior. This allows marketers to match offers and messages more closely to audience needs.
Does First-Party Data Need Enrichment?
First-party data may still contain missing fields, outdated contact details, duplicates, and limited audience attributes. Enrichment can help correct records, add useful information, improve segmentation, and extend campaigns beyond existing customer relationships.
How Does AI Affect Data Requirements?
AI can analyze and activate information quickly, but it cannot automatically correct every inaccurate or irrelevant input. Poor-quality data can lead automated systems to produce unreliable predictions, unsuitable segments, or irrelevant personalization at scale.
How Can DataPartners Prepare Marketing Data?
DataPartners can support audience planning, cleaning, matching, deduplication, enrichment, suppression, segmentation, and file preparation. The process is built around the campaign objective rather than a standard list of available filters.
Which Industries Use Custom Data?
Custom data can support broadband, telecommunications, retail, home services, financial services, B2B marketing, agencies, and other industries that require precise audience targeting.