19 questions to ask marketing attribution and predictive analytics vendors during a demo
These platforms can provide marketers with valuable insights into how to better allocate their resources.
With marketers facing increasing pressure to demonstrate the value of the budget they’re allocated for programs, marketing attribution and predictive analytics solutions are tailor-made for proving how tactics and media channels contribute to the bottom line.
Given all of that promise, marketers are certainly evaluating these technologies and one crucial part of that process is the demo. It’s important to set up demos within a relatively short time frame of each other to help make relevant
Make sure that all potential internal users are on the demo call, and pay attention to the following:
- How easy is the platform to use?
- Does the vendor seem to understand our business and our marketing needs?
- Are they showing us our “must-have” features?
Here are 19 questions to ask each vendor that will help you narrow the field:
- What platform hosting options are available (SaaS/cloud/on premise)?
- What are my options in terms of attribution modeling? Is there a set-in-stone pre-set formula or can I customize it based on my own priorities?
- How do clients typically staff and manage the day-to-day operations of the tool? Do I need dedicated data scientists, or what level of expertise is needed to get the full benefit of the system?
- What different kinds of data are available for integration and for appending? Does the vendor specialize in a particular channel, vertical or campaign objective?
- How does the platform ingest and manage offline marketing data?
- How does the platform monitor integration success and/or failures, and report on data variances or anomalies?
- How does the platform handle connectors and integrations with outside martech systems? Are your “must have” integrations rock solid?
- What is the system’s approach to integrating with the specific martech and ad tech systems that your company uses? Just because a connector exists doesn’t mean it will necessarily work for your organization and how you use that third-party platform.
- How does the platform employ machine learning for data analytics, such as predicting customer trends and patterns?
- Does the platform connect directly with execution systems so that you can quickly act on insights to tweak in-flight campaigns?
- What data security regulations does the platform comply with?
- What data security certifications does the platform have?
- Can we pay the software license month-to-month? Or is an annual contract required? Is there a short-term contract or an “out” clause if things don’t work out?
- Will there be a price increase when I renew next year — if so, how much?
- What are the additional fees? (i.e., set-up costs, add-on features, API, quotas)?
- How long is the onboarding process typically? Will we have a dedicated resource? Who will be the day-to-day contact?
- What is the level of support included in the price? What support is additional?
- Who pays if your system/team makes an error?
- Will our support team work with us to test new features and assess the results?
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Marketing attribution and predictive analytics: A snapshot
What it is. Marketing attribution and predictive analytics platforms are software that employ sophisticated statistical modeling and machine learning to evaluate the impact of each marketing touch a buyer encounters along a purchase journey across all channels, with the goal of helping marketers allocate future spending. Platforms with predictive analytics capabilities also use data, statistical algorithms and machine learning to predict future outcomes based on historical data and scenario building.
Why it’s hot today. Many marketers know roughly half their media spend is wasted, but few are aware of which half that is. And with tight budgets due to the economic uncertainty brought about by the COVID-19 pandemic, companies are seeking to rid themselves of waste.
Attribution challenges. Buyers are using more channels and devices in their purchase journeys than ever before. The lack of attributive modeling and analytics makes it even more difficult to help them along the way.
Marketers continuing to use traditional channels find this challenge magnified. The advent of digital privacy regulations has also led to the disappearance of third-party cookies, one of marketers’ most useful data sources.
Marketing attribution and predictive analytics platforms can help marketers tackle these challenges. They give professionals more information about their buyers and help them get a better handle on the issue of budget waste.
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