From bottleneck to breakthrough: How to scale consumer insights across teams without losing control

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TL;DR:

Organizations struggle to scale consumer insights effectively across departments, leading to duplicate research, poor data quality, fragmented knowledge and wasted spend. This piece explores how centralizing and standardizing the insights process with dedicated insights tools, automation and structured, repeatable processes empowers non-researchers to run high-quality, agile research projects that support smarter decision making and unify insights across an organization.

Your research team is bombarded with questions — but your organization still needs answers

Centralized insights lead to a double-sided problem: centralized insights teams are overwhelmed, while other departments make decisions based on assumptions or guesswork rather than data.

Insights teams are swamped by huge volumes of data — making it difficult to act on
Other departments don’t have immediate, ongoing access to the consumer insights they need to make strategic data-based decisions.

The DIY research that often follows leads to:

Inconsistent quality and redundant spend as non-researchers struggle to effectively and ethically apply research methodologies
The potential to fall victim to issues like bias and repeat research undertaken by other departments
A struggle to integrate complex research tools into their workflows

To empower departments to run their own research projects, while protecting data quality, companies need to create repeatable, scalable research programs. In this post, I’ll show you how smart orgs scale consumer insights with structure, automation and smart enablement.

How can I build a repeatable, scalable research process?

Ad hoc research, designed to address a specific immediate need, typically requires extensive business resources and slows down decision making.

From time to expense, ad hoc surveys require teams to go through a drawn-out, multi-step process each time they want to generate new insights.

For each project, they must:

Define research objectives,
Map out their research methodologies,
Carefully choose representative samples,
Pick their data collection techniques,
Analyze their data and
And finally, draw insights from the results.

In addition, without the right systems, governance processes and robust methodologies in place, businesses may undermine data quality by focusing on research approaches that are fast, cheap and easy to use like polls with limited sample sizes and questionable methodologies.

To scale research across an organization, you don’t need more bandwidth — you need structure and solid processes. Smart orgs typically empower teams to run their own research projects with in-depth playbooks, templates that support replication with confidence and strong governance practices.

Repeatable processes, guidelines and tools that simplify and automate, alongside plug-in-and-play processes help make it easy to decentralize consumer insights, giving each department access to the data they need to make smarter, more data-informed decisions. Unlike ad hoc research — research is no longer reactive. It's proactive and ongoing. Bottlenecks are reduced, insights don't take weeks or months to access and essential data isn't locked away within data silos.

💡 Zappi in action: Zappi’s Professional Services builds standardized processes for recurring research use cases across functions. No matter your department, we can help you design surveys, build custom audiences, provide strategic guidance (including project launches and in-depth reporting) and undertake database reviews.

Our research and insights tools are underused and siloed — how do we fix that?

Research and insights tools like Zappi often sit idle because teams don’t know how to use them effectively or how these platforms can help benefit them. From building better products to guiding advertising campaigns, getting departments to use insights tools begins with illustrating their value in terms of department goals and providing tailored onboarding and support.

To use these tools effectively, teams need to go through onboarding and training that shows them how to use them for their specific use cases and integrate them easily into their day-to-day workflows. Without the right support and training, research becomes a bottleneck — teams avoid using tools or use them ineffectively and fail to get access to the insights they need to guide decision making.

💡 Zappi in action: Zappi provides several features to help teams across departments feel confident using the platform to run their own research projects. Zappi’s enablement programs, onboarding templates and embedded coaching can help support confident, consistent use across teams. Zappi provides user-friendly research capabilities and offers data insights from one centralized, customizable dashboard that’s easy for non-researchers to interpret — breaking down barriers to adoption and making it easy for each team to use Zappi to support department goals.

We need to empower non-researchers to self-serve without compromising data quality.

Whether departments want to know how to build better products, support customers more effectively or help guide prospects more effectively through the customer journey — consumer insights often give them the ability to do so. That’s why many companies attempt to empower product, brand and marketing teams to do their own research and use data to guide their decision making. But non-researchers are vulnerable to inadvertently letting data quality slip.

In fact, 65% of organizations say they believe they suffer from data bias, while 77% believe that they need to do more to address it.

Non-researchers undertaking their own research projects may unknowingly choose unrepresentative samples, fail to uphold correct data cleansing practices, misinterpret data findings, fall vulnerable to a host of data biases or choose easy-to-use tools that undermine the integrity of their chosen research methodologies. But you can’t let data quality slip. Poor quality data leads to:

Poor-quality results
Undermining the validity and reliability of departments’ research findings
Uncertainty of the reliability of departments’ research findings

When department teams don’t know how to collect, cleanse, process and analyze data, and are unaware of their own lack of knowledge or understanding, then research becomes redundant.

As an example, data bias is a huge issue even among trained researchers. Non-researchers may be unaware of the ways data bias can impact reliable data analysis and undermine the validity of research findings. They may fail to account for their unconscious perceptions of different genders, classes, races or consumers from socio-economic backgrounds. They may also be unaware of confirmation bias and their inclination to overlook any research results that do not reflect their initial hypothesis or current beliefs. And they may fail to understand how sampling bias can prevent them from collecting a representative sample of their target research population.

💡Zappi in action: Zappi's frameworks offer a standardized, templated approach that guides non-researchers through the entire research process, from choosing their methodologies and picking representative samples to data collection and analysis. Zappi was built to support agility, allowing non-research teams to quickly gather valuable consumer data without sacrificing data quality and iterate on strategic insights without extensive training or guidance from experienced researchers.

How do we drive insight adoption across global markets and business units?

Distributed teams typically lack uniformity and consistency when it comes to research. They rely on inconsistent research methods, while learning is fragmented — siloed away and inaccessible to other teams that could make use of its insights.

This often leads to duplicated spend as different units replicate similar research again and again. Data silos and fragmentation often results in conflicting views of customers and how to engage them, with inconsistent messaging and less-effective personalization. For consumer data to help support a culture of data-driven action and innovation, it must be integrated and centralized.

💡Zappi in action: Zappi was built to reduce data silos and provide a centralized hub for research findings across business units. Zappi offers a number of features to help support this including global dashboards, reusable study templates and cross-market benchmarking that help unify insights across an enterprise.