3 Key Challenges of Modern Marketing Analytics

Use Cases & Projects, Dataiku Product, Scaling AI, Featured Lauren Anderson

In today's fast-paced digital landscape, marketing analytics leaders are at the forefront of decision-making in marketing organizations. They play a crucial role in deciphering complex datasets to guide marketing strategies and drive business growth. However, this role comes with its own set of challenges that have intensified in recent years.

With an ever-increasing martech stack, the explosion of new technologies like Generative AI, and the always-present concern for customer data privacy, all combined in an environment where showing ROI is critical, this function is under more pressure than ever. 

What Is Marketing Analytics? 

Marketing analytics is the systematic process of gathering, interpreting, and leveraging data to comprehend and optimize marketing strategies. It involves the utilization of statistical methods, predictive models, and data mining techniques to extract valuable insights from diverse datasets.

Why Marketing Analytics? 

The significance of marketing analytics cannot be overstated in today's competitive landscape. Here's why it stands as a linchpin for businesses:

  • Data-Driven Decision-Making: Marketing analytics provides a data-backed foundation for decision-making, steering strategies away from guesswork and towards precision.
  • Enhanced Targeting: By analyzing customer behavior and preferences, businesses can tailor their marketing efforts, ensuring personalized and targeted campaigns that resonate with their audience.
  • Optimized ROI: Understanding the performance of marketing channels enables companies to allocate resources effectively, maximizing returns on investment.
  • Competitive Edge: Leveraging insights gained from marketing analytics enables businesses to stay ahead of the curve, anticipating trends and adapting swiftly to market changes.

Today’s Marketing Analytics Challenges

Here are three of the key marketing analytics challenges we hear marketing analytics leaders face today: 

1. You are forced to rely heavily on slow external teams for analytics projects you need done ASAP to stay relevant.

While agencies are key players in the sea of vendors marketers rely on for advanced use cases, data sharing is often limited and so they come with downsides when marketing teams want to use that data for their own analytics initiatives. This means that rich insights aren’t adequately reincorporated into owned customer data profiles, leaving gaps in customer understanding.

While you can get some quick wins utilizing agencies, when it comes to trying out your own use cases (for example, personalization or retargeting), this can drastically limit the effectiveness of your efforts. In a world where cost-cutting is king, these agencies also come with an expensive price tag. Many marketing analytics teams want to bring more of these tasks in-house for both the expense and data benefits, but there’s never enough time to do it. 

Not to mention, marketing analytics teams often lack the technical skills necessary to take on the work themselves. Typically when they do build anything in-house, they still have to rely on internal data teams to execute most of the work, who are strapped for resources themselves. This means waiting months and months in a marketing environment that can evolve at a moment’s notice. 

With CMOs pushing marketing analytics leaders to take full advantage of new technologies like Generative AI, those same skill and time limitations prevent them from doing nearly as much as they feel they should.  

Solution: Use marketing analytics tools that empower the teams you have today to tackle AI use cases on their own. Modern analytics and AI platforms, like Dataiku, have features like AutoML (Auto Machine Learning) with visual tooling which means analysts can take on more work when it comes to building machine learning models. That means your team can take on advanced use cases without the help of agencies, all while relying less on internal data teams. 

Dataiku also features a robust library of free pre-built templates for common use cases like segmentation, recommender engines, churn prediction, omnichannel marketing, and more, that you simply download and customize to your company’s needs. When it comes to the latest technologies like Generative AI, Dataiku can empower your team to securely scale your efforts beyond ad hoc tasks. Imagine creating personalized messages for an entire database of customers, versus using a tool like ChatGPT to just create a single message. 

2. You’re sitting on a goldmine of customer data you can’t easily access.

One of the most significant challenges marketing analytics leaders face today is effectively aggregating the overwhelming amount of data at their disposal. With the proliferation of digital channels, platforms, and tools, businesses are generating more data than ever before. Not to mention, many data sources may be in the cloud as part of a modern analytics stack, but teams may still be working from disparate desktop tools like spreadsheets to perform analysis.

Simply accessing all the data from multiple sources they need to get a full customer 360 view often seems impossible. Not to mention, between these tools data often requires lots of manual work to be usable. For example, the definition of “lead” or “session” may have five different definitions across five different tools, all of which have to be cleaned and joined before they can be used for analytics initiatives. 

While a portion of this data preparation is often automated, many times analysts still have to come in and make their own manual tweaks. And, automation is often fragile and prone to breaking, which leads to mistrust from the marketing, sales, and customer teams that rely on marketing analytics. All this means that actually leveraging data to gain insights is a time-consuming, tedious process that’s error-prone. 

Solution: A centralized platform that brings all your data sources together: To tackle the issue of data overload, marketing analytics leaders need to utilize platforms like Dataiku that allow them to easily aggregate data regardless of size or location. Using marketing analytics tools that are built for modern cloud analytics also means that teams can use their cloud data investments in the way they are intended.

Additionally, leveraging advanced analytics tools and AI can help automate data processing, identify meaningful insights, and reduce the manual workload. Prioritization is also crucial, focusing on collecting and analyzing data that directly aligns with key business objectives. 

3. Generative AI promises to make marketing analytics processes more efficient, but you’re not sure how to safely adopt it into marketing tactics.

Generative AI is the hottest topic of the day, and for good reason. It promises huge leaps in both accuracy and efficiency for marketing analytics and marketing campaigns. But most marketing functions are only using Generative AI on an ad hoc, one-off basis today, or in disparate tools. By putting data in third-party chat tools, you risk losing control of your data. By relegating Generative AI activities to siloed tools, which often have siloed data profiles, you reduce your overall impact and effectiveness. 

Solution: Keep data secure with enterprise-grade Generative AI. With Dataiku, you can unite your data in one place and take advantage of our secure LLM Mesh methodology to take your efforts to an enterprise-grade level. Imagine moving from having individual marketing team members create customer emails that may not resonate, to creating hyper-personalized emails for an entire database of customers in seconds. 

Or, imagine having your marketing stakeholders query an app using regular language such as, “What was the performance of the campaign from March to June?” and getting an automated response with the correct charting. Not to mention, you can further increase the internal efficiency of your teams with built-in Generative AI features that allow you to tell Dataiku how you’d like to transform data in simple language, to automate data transformations. All of this is possible with Generative AI in Dataiku. 

→ Watch the Webinar: Explore the Power of Dataiku & Snowflake to Accelerate  Marketing Efforts

Dataiku: Your New Marketing Analytics Tool  

As we look ahead, it's clear that the role of marketing analytics leaders will continue to be pivotal in helping organizations make informed decisions and stay competitive in an increasingly complex marketplace. Dataiku is the only platform for modern marketers that empowers teams to reach optimal marketing effectiveness by collaboratively building enterprise-grade Generative AI and analytics models, all with data synthesized from disparate tools.

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