Accurate data is essential to marketing operations as it powers the CMO dashboards that provide strategic financial and performance metrics. Yet, today’s reality is that companies struggle with how to leverage their data for practical implementations – whether for day-to-day marketing operations analytics or high-level insight for demonstrating marketing’s impact on the bottom line writes, Frank Moreno, Vice President of Worldwide Marketing, Datawatch

Marketers want to make data-driven decisions, but they struggle to access information and maintain high data quality to create a well-rounded picture. The self-service analytics movement allows all marketers – in fact, every business user – to access information, then blend, combine and analyze it to uncover transformational insights. But how these data sets are brought together and managed is not being done in a thoughtful and intelligent manner. Two marketing analysts could come up with completely different conclusions if the data on which their analysis rests is wrong, outdated or incomplete.

Marketing data sets are not easy to create. Salesforce, Google Analytics, LinkedIn, Google AdWords and other platforms are all formatted differently, may not provide historical data or lack the ability to be combined together in a single view. The result is a hodgepodge of various files and formats where nothing can be quickly or easily distilled into a dashboard or used to build a marketing data strategy. Marketers are left frustrated and scratching their heads on how to get a comprehensive view of all of their marketing activities. To be successful, teams must implement a clearly outlined offensive and defensive marketing data strategy from which CMO dashboards and reports can be built .

How to build the right data strategy

In a recent Harvard Business Review article, co-authors Leandro DalleMule and Thomas H. Davenport share a new approach for chief data officers (CDOs) to use when building an effective data strategy. As companies and marketing teams struggle for the best way to use their data, the authors introduce a new business-focused data strategy framework that addresses what they refer to as “defensive” and “offensive” data utilization and how to manage data to achieve each of these purposes.

This approach is unique as it requires both data governance and user agility – goals that often conflict, but can be simultaneously achieved. Data defensive is described as using data that “minimizes risk” while data offensive addresses those initiatives that “support business objectives”. While these categories provide excellent segmentation of data usage, it’s important to note that how data is used in an organization varies dramatically, regardless of its offensive or defensive position. Therefore, an additional segmentation related to operational efficiency and analytical insight is needed.

Every organization has operational tasks that are required across various roles, departments and industries. These operational tasks often entail regularly scheduled processes and deliverables, while others may be adhoc. Additionally, operational tasks may be defensive, such as compliance reporting and transaction reconciliation, or offensive like market segmentation or account penetration. Yet, regardless of whether the data is used for defense or offense, operational efficiency is essential – as these tasks are often recurring, required and possibly time-consuming.

Simultaneously, the explosion of self-service analytics has empowered individuals and lines of business to build data visualizations and execute analytics initiatives that help guide internal decisions and external strategies. Again, these analytical insights can be both defensive, such as employee retention analysis or customer renewals, and offensive analysis like market sizing or product discount tracking.

As you can see in the grid below, this data strategy has been applied to marketing metrics. This strategy clearly outlines how CMOs and marketing teams can create an approach that minimizes risk while directly supporting business objectives. It shows which data sets are the most crucial for everyday tracking, such as email open rates, while alerting marketing teams to which data analytics will impact the bottom line, like predictor-to-purchase. Based on this grid, marketers can build an effective, intelligent CMO dashboard with the right data insight.

Reporting on the right metrics

Dashboards are visual representations of the marketing strategy that executives use to ensure initiatives stay on track. CMOs use these powerful reports to get a view into marketing’s overall performance, progress towards goals and the impact it is having on the business. In fact, a recent “Market Accountability” report from Forbes CMO Practicestated that “marketers who pursue higher levels of marketing accountability are achieving five percent better return on marketing investments and more than seven percent higher levels of growth performance.” These dashboards provide a visual representation of how marketing programs are reaching those strategic goals.

Even small organizations or a small marketing department can leverage dashboards for strategic guidance because there are solutions for every budget. But make sure to read the fine print – most of the dashboards targeting marketers are incomplete and only report on part of the data metrics outlined in the grid above. These “drag and drop” and “build KPIs in seconds” claims only provide single metrics, e.g. total leads, number of demos, impressions, clicks, views, shares, etc. The numbers have no context and no strategic value that CMOs need – nothing from the top right quarter of the grid. Dashboards need to mimic reports that are delivered by finance teams with items such as cause and effect, forecasts and revenue drivers.

Rather than trying to find the “miracle marketing” dashboard that can be implemented with one click, marketing teams need to go back to the source – the data itself . With the assistance of self-service, collaborative analytical solutions, marketers can pull information from various sources and build a customized CMO dashboard with the metrics most important to their company. Many data preparation and analytical tools allow marketers to automate data collection so that there is always the most recent information for the creation of the dashboard.

Another added feature of these tools is the central data management platform. Management, departments and individuals tend to look at all of their data as a separate and distinct set of data points/metrics. Rarely do they look at an all-inclusive picture to catch trends which may cut across different datasets. Having a central data collection that paints a holistic picture, allows companies to be proactive in their approach. It also prevents potential disasters with a team view that incorporates both offense and defense in one single tool.

Pulling it all together

The movement toward intelligent data strategy is being driven by the need to provide CMOs with a smart and flashy dashboard that clarifies which campaigns are working and which ones are not. But, getting these dashboards right requires the ability to rapidly access, blend, manipulate and enrich trustworthy data for analysis (e.g., campaign, customer, web, sales, social and other data).

To evolve a marketing data strategy that can support both offensive and defensive data initiatives, CMOs should pursue team-based, enterprise data intelligence solutions – especially for marketing teams who are driven to find the cross-business insights that profoundly impact operational processes, marketing campaigns and the company’s overall bottom line.

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