Quantifying the Cross-Channel Customer Journey
As consumers engage with brands across a proliferating array of digital and offline touchpoints, marketing leaders need sophisticated attribution modeling capabilities that provide a holistic, cross-channel view of customer journeys. Cross-channel attribution, allows brands to accurately evaluate performance across their integrated marketing strategies spanning awareness to conversion.
The Goal of Cross-Channel Attribution
The core goal of cross-channel attribution is to gain clear visibility into how each marketing channel, tactic, and campaign works in concert to influence conversions and sales. Unlike siloed, channel-specific analysis, cross-channel or multi-touch attribution (MTA) takes a comprehensive approach optimized for today's fragmented marketing ecosystem.
Note: Be aware that within the industry, different marketers and martech vendors may use these attribution terms differently: multi-touch, cross-channel, omni-channel, full-funnel and full-path.
- Omni-channel, cross-channel: both of these terms are sometimes used to refer to channel attribution, i.e., attributing sales across channels.
- Full-Funnel, Full-Path: both of these can mean less than a comprehensive attribution methodology. For example, Full-Funnel could exist entirely in one channel. Full-Path can refer to the Full-Path attribution model, or what’s called a position-based Z model.
For the purposes of this post, cross-channel attribution refers to comprehensive multi-touch attribution (MTA).
Why Cross-Channel Attribution?
In today's proliferating marketing ecosystem, brands engage consumers across a myriad of digital and traditional channels spanning the entire customer journey, from early awareness to ultimate conversion. As touchpoints expand across social media, search, display ads, email, streaming video, offline media and more, marketing leaders need integrated measurement strategies to quantify performance across their complete marketing mix.
What is Cross-Channel Attribution?
Cross-channel or multi-touch attribution (MTA) provides this holistic visibility by revealing how different platforms and campaigns work together to influence outcomes. It moves beyond channel-specific or single-touchpoint analysis to provide system-wide insights optimized for today's fragmented, environment.
Rather than siloed assessments, MTA takes a comprehensive approach to quantify the collective impact of orchestrated messaging and experiences across the entire customer lifecycle. This empowers brands to accurately evaluate which integrated mix of digital advertising, broadcast, streaming video, organic search, social media, retail, and other touchpoints maximizes ROI in an increasingly complex consumer journey.
Where Cross-Channel Attribution Works
Today's consumers typically engage with a brand across multiple touchpoints spanning several channels before converting. High-value purchases in particular often involve an extended, nonlinear journey. Brands must court modern customers through ongoing, orchestrated outreach.
For example, a prospect may first hear a radio ad, then click a digital ad, visit the website, sign up for emails which they open over months, follow social media, and eventually purchase after hearing the radio ad again. The final ad triggered purchase, but the brand built familiarity and trust through prior messages across channels over time.
Cross-channel or multi-touch attribution (MTA) provides the comprehensive intelligence required to quantify the collective impact of disparate touchpoints on outcomes. Unlike flawed "last click" models or even channel-level attribution, it reveals how integrated cross-channel marketing strategies combine to influence complex consumer journeys preceding conversion. For today's marketers, this holistic view is indispensable.
How Does Cross-Channel Attribution Work?
Multi-touch attribution provides invaluable insights that allow brands to optimize both marketing effectiveness and the customer experience. By revealing which messages and channels resonate most across the winding journey, marketers can deliver more relevant outreach tailored to demonstrated preferences.
Rather than relying on intuition, cross-channel analytics quantify engagement signals to inform personalized, contextually appropriate communication. For example, analysis may uncover certain educational content types that correlate strongly with conversion - that insight can inform content strategies across channels.
While attribution does aim to optimize spending, its holistic visibility also allows delivering positive brand experiences that build affinity and lifetime value. In today's proliferating consumer landscape, data-driven personalization and coordination underpin effective engagement. Multi-touch attribution provides the customer intelligence essential for brands to understand and serve customers.
1. Capture Complete Individual User-Event Data
To optimize spending, marketers must take a comprehensive approach to attribution and quantify performance across every channel--owned, earned, and paid. Even non-advertising efforts like SEO, sales visits, or organic social engagement need inclusion to fully understand impact on outcomes.
Multi-touch attribution reveals how diverse touchpoints collectively influence conversion throughout the customer journey. Focusing solely on a few channels provides an incomplete picture missing key insights. The goal is a holistic view of orchestrated efforts spanning awareness to purchase.
With cross-channel attribution, brands can uncover surprising insights like highly influential tweets or blog posts that convert prospects who see ads. These learnings inform integrated strategies and budget decisions. For comprehensive intelligence, marketers must measure all activities influencing customers, not just advertised channels. A system-wide approach is required to realize attribution's full potential.
2. Unify All Data
Modern consumers engage with brands across integrated online and offline environments. They expect unified experiences whether shopping on ecommerce or in-store. Silos between digital and physical hamper delivering the seamless experience customers demand.
Just as users expect unified experiences, marketers must unify all user-event data and metadata in one platform. Regardless of the capture technology, the rich set of data that tells the customer’s story must be connected in order to be analyzed and acted upon. Comprehensive cross-channel attribution depends on user event data, beginning as anonymized IDs, then connecting to real prospects when they become a lead. The metadata such as campaign, ad, landing page, must be connected to the user-event. Finally, the revenue at the end must be tied to the customer.
Traditionally, cross-channel attribution or MTA was hyper-focused on the clickstream–just those marketing elements that could be captured in real time from the digital customer journey.
Now however, more brands have distributed touchpoints that include broadcast, OTT, trade shows and more. Many technology partners and software solutions capture that data asynchronously, with platform APIs or other automation tools for marketers.
Without a complete dataset, data analytics dashboards and reports provide a partial view of the customer journey and optimization opportunities.
3. Drive Action
The core goal is optimizing total return on marketing investment and not any singular channel. Cross-channel attribution provides the comprehensive intelligence required to orchestrate integrated strategies and deliver personalized messaging sequenced to each customer’s path. Nevertheless, the true measure of attribution success is driving better decisions and results for the brand and customer. To drive actions:
- Prioritize attribution insights tied to revenue and core financial metrics. Avoid distractions from vanity metrics like impressions that lack business impact. Only act on statistically significant findings.
- Build tailored attribution data reports and dashboards for specific stakeholder groups: CMOs, VPs of Sales, CFOs etc.
- Implement efficient workflows for rapidly communicating attribution insights to relevant teams and decision-makers.
- Train stakeholders on interpreting attribution data and consulting them on data-driven optimization opportunities.
- Develop agile processes for iteratively testing and learning from new attribution-informed strategies.
- Continually refine KPIs based on the latest attribution learnings to maintain model relevance to evolving business priorities.
- Leverage attribution findings to guide high-impact optimizations balanced with longer-term brand building. Avoid chasing marginal short-term wins at the expense of brand equity.
Cross-channel attribution or MTA involves compiling granular user-level data on identifiable marketing touchpoints across digital platforms. It connects these attributable interactions to downstream conversions to quantify each touchpoint's influence in driving outcomes. A core limitation is that multi-touch attribution usually focuses on digitally trackable media, not traditional offline channels like print, radio, and linear TV which lack individual-level tracking capabilities. By relying solely on attributable online events tied to specific users, multi-touch attribution lacks visibility into upper funnel brand exposures delivered through offline media. Supplementing with marketing mix modeling helps address this blindspot. While powerful, MTA does have significant requirements and some challenges:
- Collecting comprehensive customer interaction data across channels, especially offline touchpoints
- Adapting attribution models to the diverse customer journeys and buying cycles of each target audience.
- Organizational silos and lack of data sharing
- Gaining stakeholder acceptance of data-driven model insights that may contradict conventional wisdom
- Isolating the true incremental impact of marketing amidst other impacts.
- Privacy regulations tightening data collection
Alternatives to Cross-Channel Attribution
Media Mix Modeling (MMM)
Unlike multi-touch attribution, marketing mix modeling leverages aggregated non-user level data on marketing and non-marketing factors spanning multiple years to quantify channel impact on business outcomes. External variables like seasonality, economic conditions, and promotions are incorporated into statistical models revealing historical performance by channel.
Marketing mix modeling provides a holistic, longer-term view of marketing effectiveness across both online and offline media, including impression-based brand exposures not trackable at the individual level. The approach complements multi-touch attribution's granular digital journey insights with aggregate performance data inclusive of upper funnel media.
Unlike attribution modeling, incrementality testing empirically isolates the marginal impact of specific marketing efforts. Media platforms directly run controlled experiments varying ad exposure to quantify incremental outcomes attributable to each campaign. This methodology circumvents inaccuracies in modeled cross-channel attribution by directly measuring real-world results driven by granular changes in advertising exposure. Though more costly to execute, incrementality testing provides definitive performance insights to optimize channel spending.
Holistic cross-channel measurement requires investment, whether using cross-channel MTA, or supplementing with Media Mix Modeling (MMM), or Incrementality testing. However, a full MTA baseline ensures that all customer touches are measured. Once in place, MTA can be augmented with MMM and Incrementality testing.
Need Help with Cross-Channel Attribution?
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