TL;DR

How you can help the marketing team win

• Facilitate cross-team collaboration between data and marketing teams to improve data quality and, therefore, overall business results.
• Prepare your data warehouse and stack for emerging real-time data and analytics marketing use cases.
• Don’t wait until the last minute to implement new data privacy and governance solutions. The third-party cookie phase-out is already upon us. Please go nudge your company's marketing team asap! 

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Content

1. Introduction: turn challenges into opportunities

2. Patterns: what has shaped the marketing landscape lately?

3. Deep-dive: challenges and opportunities
- 3.1. Rush slowly to improve data quality and reduce costs
- 3.2. To use or not to use real-time data, that is the question
- 3.3. Cookies, nuggets, and GDPR

4. What's next: ask your marketing team these 5 questions

5. Wrap-up: one success factor to rule them all, one factor to unite them

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1. Introduction: turn challenges into opportunities

Many companies, especially in the tech sector, have experienced turbulence in the past few years. Proving value and revenue attribution is, therefore, more critical than ever for marketing and data teams a like.

For optimistic business leaders, almost every challenge is an untapped opportunity, whether it be the death of third-party cookies or friction between departments.

Want to find out how you can help the marketing team at your company succeed? If so, this article is for you.

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2. Patterns: what has shaped the marketing landscape lately??

Denise Persson, CMO at Snowflake, mentions four forces that has reshaped marketing in her blog 'Marketing Success in the Age of AI Requires a Modern Marketing Data Stack,' which inspired us to write our own deep dive. The forces are:

1. The accelerating convergence of advertising and marketing technologies
2. The advent of advanced AI tools, including LLMs and generative AI
3. Rising concerns (and regulatory requirements) around data privacy
4. The increasing urgency for a unified approach to data, a single source of truth that can be mined for accurate, powerful insights

We highly recommend you read the full article and download Snowflake's Modern Marketing Data Stack report.

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3. Deep-dive: challenges and opportunities

3.1. Rush slowly to improve data quality and reduce costs

Though marketers are rarely trained in systems architecture or data management, it is crucial for them to actively address the integration of data from diverse sources. This enables teams to use the data with greater confidence when implementing marketing initiatives and measuring the impact.

To address this, Brian Kotlyar, VP of Marketing & Growth at Hightouch, recommends data and marketing teams to team up to implement thought-through data validation processes, conduct regular audits, and establish clear data governance frameworks to identify and rectify discrepancies.

By recognizing this, smart team leads can improve marketing effectiveness and ROI by encouraging and facilitating cross-team collaboration or building cross-functional teams.

For successful team-ups, marketers must learn how to communicate effectively with data folks and demonstrate an understanding of the challenges data teams regularly face. Therfore, help your marketers with how they can break down requests into 1) the desired outcome and 2) the data points needed to achieve said outcome. By doing this, marketers will better understand their actual needs before reaching out to your team.

Kotlyar also underscores the need to move away from a scattered point-to-point model to a hub-and-spoke architecture that marketers set up themselves for a more warehouse-centric structure with the data warehouse as the hub. The more traditional point-to-point model spreads out and connects data through different tools, resulting in higher complexity and costs. On the other hand, hub-and-spoke architecture can offer several advantages, such as:

• cost reduction
• tool consolidation
• increased effectiveness
• swifter adaptation to new technology changes

Although there may be an initial learning curve, the Swedish saying "rush slowly" (skynda långsamt) reminds us that the time invested upfront pays dividends in the long run.

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Simply put: help your data team by helping the marketing team better understand what's going on 'under the hood'. This will reduce overall friction between the teams.

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3.2. To use or not to use real-time data, that is the question

Timely insights are crucial for accurate decision-making in today's fast-paced digital world. Yet, many businesses do not prioritize or proactively use real-time data and analytics, resulting in missed opportunities and, consequently, missed revenue.

Rob Meyer, VP of Marketing at Estuary, has observed a rapid increase in new and rediscovered use cases where real-time data takes center stage. By working your way backwards from what your company does in real-time, or even better, what competitors do, you can uncover new ways to leverage real-time analytics to improve your operations — including marketing effectiveness and spend. A few examples are:

• Dynamic funnel strategies: implementing dynamic cross-selling or up-selling throughout the customer journey requires instantaneous insights into customer behavior and preferences.
• AdTech for online advertising: (re)targeting customers with online advertising is a classic example where real-time analytics plays a pivotal role.
• Customer support tools: the most effective marketing teams focus on the entire customer journey, from "cradle to grave", and many marketing-owned channels act as support channels. Real-time analytics can provide immediate solutions to customers' issues and is, therefore, a golden source for both customer support and marketing teams.
• Unique marketing content: the combination of real-time data and generative AI opens up a world of opportunities for hyper-personalized and individually unique experiences - at scale and with rapid speed.

One of the most well-known use cases for real-time analytics is Amazon's personalized e-commerce experience. Originating from the AdTech sector, their real-time approach prioritizes speed and dynamic content. It swiftly analyzes and targets customers with features like 'other products you might like.'

Meyer highlights that, generally, data warehouses are not geared towards real-time analytics. However, in the very near future, your data warehouse (and stack) must evolve to support emerging use cases and technologies if you want to stay competitive.

If you want to level up your real-time data game to get ahead of your competitors, Estuary helps teams move and transform your data from where it is to where you want it to be in milliseconds - without scheduling.

Simply put: brainstorm with marketing on new data use cases. Together, you might figure out new ways to, for example, catching leads in real time. It's always a win-win when the company excels.

3.3. Cookies, nuggets, and GDPR

Privacy concerns and regulatory changes present new challenges for all teams, including the ongoing phase-out of third-party cookies. Many marketers anticipated this, but a remarkably large group lags behind. We saw the same thing happen with the shift from Universal Analytics to GA4, which put a strain on data teams as well. If your company wishes to continue providing tailored experiences and relevant advertising, it needs to explore new formats and tactics sooner rather than later. Areas to look into:

• Contextual ads
• First-party data collection
• Privacy-centric conversion APIs
• Predictive analysis

To make the ride less bumpy, marketing and data teams will have to work closer than ever, according to Kaustav Mitra, co-founder of Paradime. Marketing teams will own the "what" of privacy, security, and governance, while analytics teams will own the "how".

Analytics teams will need to think about data masking, data sanitization, and applying additional context from privacy-centric APIs and consent management systems as they think about modeling the data for marketing activations, Mitra explains.

There will always be policies for data handling and storage, but applying them consistently, reliably, and accurately will remain a challenge for marketing and data teams alike.

Kotlyar also stresses the importance of obtaining explicit consent, implementing robust security measures, and establishing clear policies for data handling and storage. Adhering to regulations such as GDPR and CCPA mitigates legal risks. It fosters a more transparent and ethical approach to data usage - a factor that can influence whether customers choose to buy or not to buy your product.

4. What's next: ask your marketing team these 5 questions

1. Are we collecting and processing the right data, and is it accurate? If not, what steps can we take to make it better?
2. What does our MarTech stack look like, and how does it fit with the broader data stack?
3. How can I enable and promote cross-team collaboration?
4. How can we ensure our plan for data security and privacy is implemented effectively and accurately - and ASAP?
5. Do we regularly assess and fine-tune our marketing budget based on data and insight?

Need help figuring out where to start? While we might not be able to solve all challenges, Paradime offers teams an easy-to-use solution, handling every aspect of their analytics development workflow. We help data and analytics teams reduce cost, context switching, and unnecessary complexity, while giving a 99.9% uptime guarantee. With our free collaboration plugin SynQ, your organization can bring the marketing and data and analytics teams closer in a single, collaborative communication flow.

If your team is looking to get fresh and accurate customer data in all of your tools, Hightouch, one of our integration partners, can help you sync your data with CRM, email, advertising tools, and more. No engineering, manual work, or costly Consumer Data Platforms (CDP) required.

5. Wrap-up: one success factor to rule them all, one factor to unite them

In 2024, marketing and data teams must tackle these data and analytics challenges together to seize exciting new opportunities, and therefore bring value to the organization as a whole.

• Improve data quality and access
• Experiment with innovative real-time tactics
• Effectively, and rather urgently, find solutions for privacy concerns and regulations

Encouraging proactive and mutually respectful cross-functional collaboration will reduce friction and improve the overall outcome for all teams involved.

Meagan Eisenberg, CMO at Lacework, shared valuable insights on the podcast 'Super Managers - Driving Change Forward: How to Achieve Buy-in as a Marketing Leader.' Eisenberg emphasized the need for effective collaboration, such as increasing face-to-face time, conducting one-on-one meetings, and practicing active listening. The key to building trust is delivering results, maintaining respectful communication, and providing timely feedback.

To sum up, cultivating strong cross-functional relationships is crucial to achieving operational and cultural success in the workplace.