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Blog / Cross-Team Collaboration: How to Drive a Unified Customer Experience

Cross-Team Collaboration: How to Drive a Unified Customer Experience

In the modern world, convenience is a priority. Customers want seamless journeys where brands offer the right information in the right place at the right time, and anything that introduces friction into the mix can prove fatal to the customer journey. 

However, in order to create a cohesive customer experience, businesses first need to break down silos between the teams which manage the many different touchpoints that a customer might interact with — and that means getting all their departments working together like a well-oiled machine. For marketing and sales teams, this can mean moving away from a focus on acquisition to think more broadly about customer lifetime value.

Over the course of three episodes, the Now, Next, Future series tackles the key action points that marketers need to be taking now and initiatives that they need to put on their roadmap to stretch budgets further without hampering the long-term success of their business. Check out a review of the first episode below, or download the full ebook with all three episodes here



Unlocking the power of data insights through team alignment

Mounting evidence has demonstrated the benefits of uniting efforts across marketing and sales teams to drive a more unified customer experience. Aligning teams to deliver these valuable experiences drives efficiencies, revenue growth, and increases acquisition, so it’s no surprise that David Walsh, Head of Customer Insights for EMEA and LatAm at LinkedIn, names this as the key priority for clients in 2023. 

However, it’s no small feat. In fact, one of the key challenges in the current marketing landscape, particularly in B2B where customer journeys can take many months, is this holy grail of achieving alignment across different departments. Mitesh Lakhani, Director of Solutions Consulting at Adverity explains, “You've got different teams that have completely different goals that they need to achieve, and they're not always in sync with one another.” 


cross-team collaboration cogs

Teams across the business need to be in sync with each other to create a unified customer experience.

When it’s done right, cross-team alignment can be incredibly powerful, “The sales team and the pre-sales and the aftercare team are all talking to one another as if they are part of a larger pitch team.” says Mitesh. But in order to get everyone singing from the same hymn sheet, there needs to be clear and open lines of communication between teams. 

5 challenges to alignment

This unified approach creates a lot of value, but it can be tricky to master. David identified five areas of challenge that need to be addressed in order to successfully pull the strategy off and align efforts across marketing and sales.

1. Cultural alignment

Sales and marketing teams often speak different languages. They have different goals, different objectives, and different KPIs. To unify efforts, they instead need a common goal and a common language of data.

2. Aligning accounts

Teams must also work together to define their ideal customer profile and identify high-potential accounts for collective targeting while ensuring consistency in messaging.

3. Personalization

Functions must collaboratively figure out how to use data and insights to create more effective, personalized solutions for addressing specific client needs and challenges.

4. Availability of resource

Particularly in the current climate, finding the resources to put the technology stack together that allows functionalities from different teams to communicate can be tricky. A modern tech stack needs to help functions collaboratively uncover and meet consumer needs.

5. Measurement

Establishing a unified measurement framework to consistently methodology to quantify ROI and gauge the success of alignment efforts.

Building block 1: Tech - Where does the data stack fit into the alignment strategy?

At the heart of solving these issues is finding a common language through data, and that means making sure that reliable and consistent data insights are available across the company to inform success. 

“I think that a critical part of your data strategy is getting the right data in place to really inform measurement and attribution for your marketing investment,” says David, “Finding the right data is absolutely critical, and having the analytic capabilities around that I think is super important. To be a data strategist about how you create and maintain a strategy across the business, there are four areas for that strategy.”


  1. Actionability - Can you use your data to inform decisions?
  2. Relevance - Is the data contextually relevant to the organization and the category you operate in?
  3. Evolution - How can you continue to update your data strategy based on the changing needs of the business?
  4. Integration and Connectivity - Does your data strategy connect and integrate across the organization? 

A successful data strategy is an essential tool for modern marketers, helping them to pinpoint and connect with the high-propensity audiences that are going to drive long-term sustainable value for the business and measure the success of that. 

Securing the right data stack is essential, but it’s just one piece of the puzzle. Marketers also need to ensure that they’re instilling a data-driven culture, and allowing individuals the autonomy to act on data insights — and both of these can be addressed, at least in part, through the tech selection process.

How can rethinking tech selection drive alignment?

Fostering united cross-team efforts offers huge value, but it takes time and resources to build a data-driven culture and a tech stack to support this strategy. David and Mitesh highlight four tips to keep in mind.

Tip 1 - Know what you want the business to achieve and work backward 

To select the right technology, you need to first know what end goal you want to achieve as an organization. Then it’s a case of working backward from that to land on the missing piece of the jigsaw — the technology.

“To me, it's all about use cases,” says David, “be very, very specific about use cases, and then think about how the technology is going to solve that particular challenge within the organization.”

Tip 2 - Make sure multiple teams have a stake in procurement

For technology to drive alignment, collaboration from the beginning is critical. “If technology is forced upon you with an organization, it always takes longer to adapt to it. Getting buy-in from all areas on a piece of tech or a strategy is the best way to drive a positive change within the organization,” Mitesh explains, “When you have multiple teams involved in the procurement of technology, that always equates to something that will prove successful.”

Tip 3 - Remember who the end user is

Tech procurement decisions are often made by a buying committee, especially in the B2B world. Procurement, Finance, Sales, Marketing — they’re all involved, and while we’ve established that getting buy-in from all these departments is key, it’s also important to carefully consider the end user, and make sure they’re involved in that system too. 

What are Marketing Data Analytics Models, and How Can They Optimize Campaigns blog hero

Remember to keep your end user in mind when planning out data architecture.

“Keeping the end user in mind is really, really important,” explains Mitesh. “Often the people procuring the technology and the people who are going to be using technology are two different groups. As long as they've got a harmonious relationship and can come to a compromise where both teams are happy with the end result of selecting that right technology, I think you're onto good footing there.”


Tip 4 - Think like the 76ers

“When I think about great collaborative uses of data, I think of the Philadelphia 76ers basketball team,” says Mitesh. 

The marketing team realized that insights they were using around the predictive stadium attendance for game days in the back office could be translated all the way down to the hot dog stand within the stadium itself. “It’s a really collaborative and collective use of data across the business that I think is a great advert for the way that a business should run,” says Mitesh.



Building block 2: Culture - Creating a data-driven culture from the top down

To create a data-driven culture where cross-team alignment can thrive, senior stakeholders need to set the tone and make sure their messaging around the new strategy reaches every corner of the business. “When it comes to building that data strategy. I think it comes from the leadership within an organization,” says Mitesh. ”Live and breathe it via the communication. The technology that's being used needs to be seen to be used at the very top for it to filter down across the organization. When you're living and breathing a data strategy, that's going to dictate the culture within the organization.”

Tech doesn’t just belong to the IT department anymore. As marketers continue to prove the value of a data-driven strategy time and time again, we’re now increasingly seeing a cultural shift as data and analytics become a bigger part of decision-making across all the functions within businesses.

“Culture doesn't exist in words on a wall,” warns David. “To me, it's all about a sense of belonging, a sense of being part of an organization. And obviously, data plays a key part in our organization. I think a big change is that we've seen analytics become part of multiple parts of the company.”

Building block 3: People - Twinning data science with decision science

Having a data stack and data culture that unites your teams is an important piece of the data strategy puzzle, however, data insights alone aren’t enough to effect change. For individuals to understand and act on data insights, data storytelling is another important piece of the puzzle. 

“When I think about what my team does, we produce research and insights, but ultimately the goal is to drive an action. We're trying to change behavior. We are trying to better inform someone, change a perspective, shift a viewpoint, drive a change, and support an investment decision.



“It’s in part about decision science rather than data science. We're trying to inform people's decisions. And part of those decisions are driven by emotion. I think it's those stories that are really important.”

A key part of affecting decision-making is figuring out how to humanize data and deliver it in a way that connects with individuals on an emotional level to trigger a decision — whether that’s selling a data strategy to your teams, or approaching a prospective customer with a B2B solution. Converting data into actionable insights has long been a priority of marketing teams across the globe, and one of the most effective ways to do this is through data storytelling. 

“Building data stories and creating emotional provocation is kind of how you can really drive change. And so to us, data storytelling is super important. That's what we truly believe is going to drive fundamental influence and change in organizations in the future,” says David. 

Data storytelling is the ability to communicate insights through data that lead to actions that will positively affect the business. The measurement of success for effective data storytelling however is not simply the act of sharing insights — but that actions are taken because of these insights. 

For example, as a marketer, data storytelling means being able to show how your marketing performance is impacting sales and then using those insights to enable better planning and optimization of not only your marketing campaigns but as a strategic revenue driver across the business from sales strategy to logistics.

Creating space for experimentation

A good data strategy aims to uncover valuable, actionable truths within your data, and an essential part of this is creating space for experimentation. Good data storytelling hinges on giving enough time and space for credible data experiments. Without space for experimentation, a data-driven culture can backfire. 



Marketing teams need to create space for experimentation.

Marketers working within a business that doesn’t allow for a culture of experimentation will often find themselves in a time crunch at the end of a quarter, pressured to fit numbers into the narrative that senior management wants to see, rather than the one that needs to be told. 

A crucial and often overlooked step in the cultural shift towards team alignment involves allowing teams enough autonomy to experiment and act on data. Mitesh explains, “When we've got an overarching goal or something to achieve, which is again part of that data strategy, I feel like leadership teams need to allow the teams that work underneath them to independently get to those goals how they see fit. And I think that autonomy allows for a more positive culture to be built, but it also fosters innovation.

“Research has shown that 40% of marketers are also struggling with measuring ROI. I think this is a side effect of not spending enough time with those data experiments. If more time was given, that challenge could be alleviated and a more holistic data story could be told, rather than retrofitting the data to the narrative that someone might have.”

When businesses prioritize short-term thinking, they lose the benefits of viewing their data more holistically to uncover long-term trends. If you’re running a campaign in multiple areas, across multiple channels, and with multiple creatives, it might be tempting to shift your budget at the first sign of fluctuations in performance. However, Mitesh advises that reacting too hastily can undermine the integrity of your data experiment. 

Unlocking unified customer experiences

The journey towards cross-team alignment for a unified customer experience is rife with challenges, but the potential rewards are immense. Key challenges, from cultural alignment to resource availability, underscore the complexity of this endeavor. However, the pivotal role of data in this strategy cannot be overstated. A well-executed data strategy empowers modern marketers to connect with high-potential audiences, drive sustainable value, and measure success effectively.

Yet, data alone is insufficient. Effective data storytelling, a blend of data science and decision science, is essential for turning insights into actionable decisions. It humanizes data, making it relatable and emotionally resonant.

Rethinking technology selection and fostering a data-driven culture from the top down are critical aspects of this transformation. Collaboration, clear goals, and end-user perspectives must inform technology procurement, while leadership sets the tone for a data-centric culture. Lastly, experimentation within a data-driven culture is vital for holistic understanding and informed decision-making. Rushed decisions can undermine the integrity of data experiments.

In this ever-evolving landscape, embracing these elements becomes not only a strategic choice but a cultural shift that can propel organizations to new heights of success. Cross-team alignment, data-driven strategies, and effective data storytelling are the building blocks of a brighter future in business.


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