Bring marketing, customer, and sales data together for insight into performance, customer behavior, orders, revenue, and targets.
Marketing usually has no shortage of data. Campaign platforms, websites, CRM, e-commerce, orders, and customer databases all generate figures. The challenge is that each system tells only part of the story, and definitions do not automatically align.
In practice, we mainly see these problems:
Campaign, website, CRM, and sales data are often viewed separately. This shows what is happening within a channel, but not always how marketing activities relate to customers, orders, revenue, and repeat purchases.
Exports from different systems are combined in spreadsheets, definitions are reapplied, and the same report is rebuilt every week or month. This takes time and makes analyses prone to version discrepancies and errors.
Marketing tools are effective at measuring reach, traffic, and conversions within their own channels. Answering questions about order value, customer type, repeat purchases, product mix, or final revenue usually requires additional data from other systems.
Targets are sometimes stored in spreadsheets or separate planning files, while actuals come from the online store, CRM, or ERP. This creates extra work when regularly comparing performance against targets, last year, or previous periods.
A customer, order, conversion, revenue amount, or repeat purchase is not always defined consistently across systems. This leads to debates about the figures, when Marketing wants to investigate what is changing and where adjustments can be made.
An advertising platform can clearly show how much reach, how many clicks or how many conversions a campaign generated. A web analytics system shows what visitors do on a website. But many commercial questions begin where those insights end.
Which customers actually make a purchase? Which products do they choose? What is the order value? Do customers return later? Which promotions do they use, and how is revenue developing compared with the target or last year?
Connecting marketing data with customer, order, product and financial data provides a broader view of marketing performance and commercial results.
A marketing dashboard becomes more useful when a click, lead or action can be tracked through to customer behavior and commercial results.
From an analytics perspective, marketing does not end at the click or conversion if the commercial outcome is recorded elsewhere.
Depending on the process, the journey may run from campaign and visit to lead, customer, order, revenue and repeat purchase. Not every element needs to be in a single system, and not every organization uses the same funnel.
By linking the relevant steps, Marketing can analyze where demand originates, how customers convert, what revenue follows and how customer behavior develops over time.
This shifts the analysis from isolated activities to their contribution to broader commercial goals.
How are activities and results developing in relation to goals?
Combine available campaign, website and conversion data to compare performance across periods, channels, campaigns or target audiences. The analyses that can be performed depend on the data made available by the platforms in use.
Compare revenue, orders or other relevant KPIs with the target, last year or previous periods. Analyze where performance differs and drill down by site, customer group, product or promotion, for example.
Who buys, returns and responds to which promotion or proposition?
Analyze new customers, repeat customers, order frequency, average order value and revenue from returning customers. Compare customer behavior across segments, periods and other relevant dimensions.
Examine differences between B2B and B2C, regions, sites, customer groups or other segments, for example. Where possible, connect customer behavior to orders, products, promotions and revenue.
What happens to orders and revenue after a marketing activity?
Track order volumes, revenue, and average order value, and analyze differences by customer type, product, period, site, market, or other relevant dimension.
Analyze the use of vouchers, discount codes, or other promotions, the orders to which they are applied, and how this develops over time. This allows you to assess a promotion not only by its use, but also in the context of commercial performance.
How do you bring marketing performance, customer behavior, and commercial results together? In our interactive Power BI demo, you can explore how three fictional online retailers track campaigns, conversions, return on ad spend (ROAS), customer value, revenue, and targets.
Discover which channels perform best, where conversions are lost, and how marketing activities contribute to business results.
Marketing information is rarely stored in one place. Campaign and website data resides in marketing platforms, customer data in CRM systems, transactions in an online store or ERP, and targets sometimes in spreadsheets or other planning files.
We can combine relevant data sources into a model that consistently uses the same customers, orders, products, campaigns, sites, and periods. The integrations required depend on the questions Marketing wants to answer and the data made available by the source systems.
This can create one coherent view of:
The value lies not in creating as many integrations as possible, but in carefully connecting the data needed to answer a specific marketing question.
Marketing performance often becomes more insightful when you can examine what customers actually do. Not just how much traffic or response a campaign generates, but also which products customers buy, the value of their orders, and whether they return later.
Compare new and returning customers, analyze order frequency and average order value, and examine how customer behavior develops by period, customer type, or segment.
Analyze revenue and orders by product range, product category, product, or other commercial classification. Combine this with customer groups, sites, or periods to better understand the differences.
Track the use of discount codes or vouchers, analyze their validity and usage where relevant, and link promotions to the associated orders and commercial results.
A target only becomes meaningful when you use the same definition, period, and breakdown for the actual results.
Marketing objectives are not always recorded in the same system as the actual results. By bringing targets and actual results into the same data model, differences can be analyzed directly.
This could include revenue, orders, customer growth, or other KPIs relevant to the organization. Compare the current year with the target, the previous year, or earlier periods, and drill down as needed by site, product, customer group, region, or other dimensions.
This turns periodic target reporting into an analysis that also allows Marketing to investigate where a variance arises.
The same customer may be a target audience member or lead in Marketing, an opportunity in Sales, and appear as an order and revenue in operational and financial systems after making a purchase. If each department uses its own definition and dataset, comparisons become unnecessarily difficult.
When leads and sales follow-up are part of the process, Marketing can be aligned with the same customer, pipeline, and revenue definitions used in Sales analytics.
When revenue, margin, or budget is relevant, commercial results can be linked to the definitions and data also used in Finance analytics.
This gives each department the level of detail it needs, without Marketing, Sales, and Finance maintaining different versions of the same commercial reality.
Marketing teams view the same customer journey and commercial results from different perspectives. Management wants an overview and insight into progress, specialists want to be able to drill down, and Marketing Operations wants definitions and data to remain accurate behind the scenes as well.
Marketing Management wants to know how results are developing and where adjustments are needed. This includes:
Performance and digital marketers want to compare, segment, and search data quickly. This includes:
Marketing Operations and CRM focus on the data and processes behind the analysis. This includes:
Good marketing analytics does not start with a standard dashboard, but with the questions Marketing wants to answer to guide its decisions more effectively. We then bring processes, definitions, and data sources together and build a solution that fits the existing organization.
We start with the most important marketing questions. Which results do you want to track? Where is the connection between activity and commercial results missing? Which analyses currently require a lot of manual work?
We also agree on definitions for concepts such as customer, order, revenue, conversion, repeat customer, target, campaign, and segment. This prevents different reports from each using their own starting point.
We connect the data sources needed for the issue at hand. These may include marketing and web platforms, as well as CRM, an online store, ERP, order data, customer data, product information, targets, spreadsheets, and other operational sources.
We ensure that keys, periods, customer definitions, products, sites, and other dimensions are aligned in terms of meaning.
Based on this, we develop dashboards and analyses for areas including:
Which elements are relevant depends on the commercial process and the available data. We do not add a measurement model simply because a platform can provide the figures.
Depending on the existing environment, we work with Qlik, Power BI, Microsoft Fabric, TimeXtender, or a combination of these.
If you already have an analytics environment, we build on it when that makes sense. We can improve existing models and dashboards, add new sources, harmonize definitions, or support a migration. If you are unsure about the current approach, a Second Opinion Data & Analytics can be a good first step.
After delivery, we can also support and manage the environment, so that new data sources, analyses and changes can be added in a controlled way.
For one organization, we developed a marketing analytics solution that combines data from multiple sources. Among other things, the marketing team can compare revenue trends with targets and previous periods and analyze orders, products, customer groups and geographic dimensions.
The solution also supports the analysis of promotions and vouchers and distinguishes between new and returning customers. This allows the marketing team to drill down from a comprehensive view to the underlying customers, orders and commercial patterns.
The relevant sources vary by organization and marketing challenge. The required information is often spread across different types of systems.
Campaign platforms, web analytics, marketing automation, email marketing and other digital marketing sources.
Leads, customers, segments, contact details, commercial history and other customer-related information.
Orders, order lines, revenue, products, prices, discounts, order statuses, sites and other commercial transaction data.
Targets, budgets, spreadsheets, databases, APIs and custom systems containing supplementary information.
Many marketing teams already have dashboards, reports, spreadsheets and platform reports. The question is usually not whether everything needs to be replaced, but where the current view falls short and which integration or improvement will deliver the most value.
For example, we can:
Even if the data is not yet fully in order, an initial analysis can still be valuable. It reveals which missing integrations, definitions and data quality issues affect the reliability of the most important marketing analyses.
A good marketing solution does not need to measure everything. Above all, it should help answer the questions that Marketing actually wants to use to guide decisions.
That depends on the questions you want to use to guide decisions. Marketing data may be sufficient for campaign or website analysis. To gain insight into customers, orders, revenue, products or repeat purchases, you will generally also need data from CRM, e-commerce, ERP or other commercial systems.
Yes, provided the necessary data and linking fields are available. We can combine marketing and customer data with orders, revenue, products and other commercial data. The exact relationships we can establish depend on the configuration and quality of the source systems.
This is possible when campaign, channel and conversion data can be reliably linked to subsequent steps in the commercial process. We first determine which identifiers and definitions are available and avoid using an attribution model that suggests more certainty than the underlying data supports.
Yes. When customer and order history are available, we can distinguish between new and returning customers and compare metrics such as revenue, order frequency and average order value. We define exactly what constitutes a returning customer in advance.
Yes, if this information is available in the source data. We can analyze aspects such as usage, quantities, validity, discount amounts and the associated orders, and highlight differences between periods, promotions or customer groups.
Yes. Targets from a file or planning source, for example, can be compared with actual results. This allows you to analyze variances across the same periods and dimensions, such as by site, market, product group or customer segment.
Yes. Shared definitions are particularly valuable for customers, revenue, orders and commercial KPIs. Each department can have its own reporting and level of detail, while the underlying data and definitions are managed centrally.
Yes. We can assess and improve existing dashboards, data models and KPI definitions. This may involve missing data sources, manual exports, inconsistent definitions, slow reports or insufficient integration with customer, order and revenue data. If you are unsure, a Second Opinion Data & Analytics can be a good first step.
That depends on the existing environment, information needs and desired solution. We work with technologies including Qlik, Power BI, Microsoft Fabric and TimeXtender. We prefer to build on what is already in place.
No. A clearly defined question can be a sensible first step. Examples include revenue versus target, analysis of new and returning customers, promotion analysis, or connecting an existing marketing dashboard to order and customer data.
That depends on the number of data sources, the quality and history of the data, the required analyses and the complexity of the integrations. A clearly defined report can be delivered through a manageable project. A broader solution that connects marketing data with CRM, orders, products and financial data requires more analysis, modeling and coordination.
No. Marketing analytics is broader and can include customer behavior, revenue, orders, products, targets, campaigns, and promotions, among other things. Attribution is one possible component and attempts to attribute commercial results to marketing touchpoints. Whether this can be done reliably depends heavily on the available tracking and customer data.
Would you like to better connect marketing data with customers, orders, and revenue, improve existing reports, or answer a specific marketing question using a single reliable data foundation? Barry and Eric would be happy to discuss your current environment, information needs, and a logical next step. In half an hour, you’ll know whether we’re a good fit. Email us, call us, or schedule a call right away.
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