In addition to being critical to revenue and sales optimization, data is one of the biggest sources of noise. It’s often challenging to translate signals into a clear market story—and even more challenging to reposition these insights into action.
The right path forward means knowing what to avoid. Here are the biggest risks that CMOs face when choosing an analytics solution.
Many cloud-based analytics platforms make big promises to measure customer lifetime value, predict customer behavior and optimize revenue. While these value propositions sound strong in theory, they often miss the mark in solving practical problems with fully baked software solutions.
The reason why is that simple—data science is an extremely new field, and many analytics tools are still in their infancy. Platforms may promise product features that appear accessible but are actually delivered through expensive, manual projects. Make sure that you’re working with an established, productized vendor by asking the following questions:
- Can you login, demo your product, and align features to a marketing use case?
- Can you walk me through a clear customer success story and what role your software played in the process?
- What is the methodology and differentiation behind your analytical assumptions and calculations?
- What target market do you help me analyze and why?
- What types of customers aren’t a fit for your platform?
As data science and SaaS analytics markets begin to mature, companies will need to adapt to very precise company needs. Make sure that you’re choosing a partner that understands and builds around the needs of your organization, in-depth.
One of the biggest challenges, when it comes to successful marketing analytics technologies, is implementation. Between tracking pixels and dynamic buyers to integrating CRM data, marketing analytics systems have many moving parts.
When vetting technologies, CMOs should develop a clear picture for timelines and technical resources required to get up and running. Here are the most important questions to ask potential partners:
- Can you walk me through a past implementation experience with a company of my type and size?
- How much time and what organizational resources will be required for implementation?
- Do you offer a trial or proof-of-concept that my team can easily access before purchase?
- After the initial implementation, will my system self-learn and update? Or will further maintenance by experts or consultants be required?
- Is there a customer success team or just engineers?
CMOs should seek out resources that can be easily implemented and tested without heavy commitments from IT, engineering, and wallets. Solutions with the most sustainable and highest possible performance are also those with the lowest possible touch.
The hard truth is that many marketing tools aren’t built for running rich or granular segmentation analyses. Systems might be antiquated and unable to rely on the multiple information sources required for making informed business decisions—third party providers, first-party data, and real-time feedback.
It’s important to choose systems that can leverage these different information sources in an efficient and impactful way. Otherwise, you’ll risk making decisions from analytics that rely on inaccurate data intelligence. And beware of opting for short-sighted enrichments or CRM data appends, which not only fail to provide marketers with analytics, but can also create problems within your system from stale, static data. Avoid this pain point by asking your partners the following questions:
- How comprehensive is your platform’s matching technology? Does it rely on exact matches to unique identifiers like emails? What are your average match rates?
- How granular are the segmentation and targeting capabilities? Does it allow my team to run assessments for any market opportunity?
- What are the most creative challenges that your customers are using your platform to tackle?
The bottom line is that you need to choose systems that can grow with your business. Focus on scalability, integration with other sources of data, and actionability of the analytics. You can take an extra step to vet your partner’s technical infrastructure by asking your engineering team to join your initial discussions.
The best vendors are always learning and growing. Look for analytics providers that have experience working with and providing solutions to companies like yours. Don’t reinvent the wheel. The best partners are ones that will have spent years studying the exact pain point that you’re looking to solve.
To navigate the process of finding the right analytics technology, visit Radius—predictive marketing software that transforms the way B2B companies discover markets, acquire customers, and measure success.
When measuring the effectiveness of discount codes, retailers often get it wrong. In this article, we'll look at how data-driven attribution can help businesses better understand where discount codes produce the best ROI.
Data. It’s the latest ‘buzzword’ in the digital marketing world when it comes to content.
The term ‘marketing cloud’ has gained significant traction in the last few years as major software companies have sought to monetise the growing importance of technology for marketing teams.
Digital has quite forcefully overturned the entire media industry, causing even the most traditional companies to adapt or be left behind.