The six biggest myths holding back insight-driven businesses

The six biggest myths holding back insight-driven businesses Data-based efficiency has driven every stage of Alex’s career. From the creation, growth, and successful exit strategy applied to the multiple companies he has been involved with, to his current role as co-founder and CEO of intelligence platform Adverity, powering smarter decisions with accurate analysis remains a key passion for Alex. Adverity is an intelligent marketing analytics platform specializing in enabling data-driven marketing teams to make better decisions and improve performance, faster and easier. By transforming siloed data into actionable insight, Adverity reduces the complexity involved in demonstrating the return on investment of multichannel marketing spend.

Between economic pressures and ever-dynamic consumer trends, the past year has driven businesses to be more agile. If we’re looking for a silver lining to the pandemic, it’s that companies have accelerated their journeys toward data maturity.

But what does this mean for marketing operations? Despite the challenges, more and more businesses have turned to data to help reframe their priorities and achieve greater agility. While financial investment in this area is high – over three-quarters (76%) of ‘data-driven’ businesses plan to continue spending on data skills training – simply committing budget to new tools or development is only part of the process.

To become truly insight-driven, organisations must do more than overcome a few hurdles in the hopes of reaching the finishing line. The path to data maturity is complex and evolving, with no definitive end point. Businesses from all sectors need to continuously audit, assess, and review progress along the way – and as they move forward, they must ensure they aren’t blindsided by the key misconceptions around what insight-driven really means. Here are some of the most common myths we still see upheld, every day.

Myth #1: Technology will boost success overnight

Forecasts predict the global market for big data and business analytics will surpass $512bn by 2026, as companies of all sizes ramp up their spend in new technologies. However, organisations can often prioritise having the latest tools over using existing ones more effectively.

And while technology is important, true insight-driven agility depends more on the mindset of an organisation than the calibre of its technological toolbox. For example, Gartner suggests that ‘data blindness’ is a roadblock keeping organisations from being insight-driven when it comes to identifying and assessing skill sets – if a company does not have the right team, knowledge, and even culture in place, progress can be difficult.

The journey to data maturity always begins with taking stock of current systems, assessing how they interact with each, and identifying potential gaps – whether that’s tech or talent.  Only once this audit has taken place can organisations make informed decisions on the next best action for their business or team. Simply investing in the latest technology is not a magic bullet to become an insight-driven business overnight.

Myth #2: Dashboards are a one-stop solution

While dashboards are undeniably beneficial for quickly visualising data in a user-friendly format, maximising their value relies on how they’re employed in the decision-making process and where a company sits in its data maturity journey. For a company early on in their data journey, dashboards can help them to make sense of the data they have, bringing order and time benefits – while also connecting teams across the business. However, dashboards should not be viewed as static tools: the most successful dashboards are those that evolve alongside the organisation, and that depends on the know-how of the teams using them.

For companies further along in their data maturity journey, future-focused insights hold the most value and dashboards can be used alongside predictive analytics, allowing teams to be proactive rather than reactive. Algorithms can help companies to identify hidden anomalies and visualise trends that may have otherwise been missed – and marketers can use these insights to guide their decision-making, whether that’s redistributing marketing spend to the best performing channel or optimising strategies based on contextual factors.

Myth #3: More data means more accuracy

By leveraging the wealth of data and embracing the power of predictive analytics, it’s possible for marketers to uncover new opportunities and answer key questions before they’ve been asked. However, marketers’ appetite for data across multiple channels has resulted in businesses tapping more and more data streams without first optimising those they already have. The truth is, not all data is good data. Businesses need to ensure their data is relevant, cleaned, and harmonised before relying on it to generate insights.

In short, focusing on quality over quantity delivers better outcomes. Insights based on quality data offer decision makers greater certainty when implementing changes in-flight or planning new strategies – a form of marketing insurance. Ultimately, driving effectiveness comes down to how businesses leverage their data as opposed to the volume that is collected.

Myth #4: Businesses only need marketing data for decision-making

That being said, another common myth is that data collected from marketing applications is the only data a business needs to make more strategic decisions. Although companies don’t need masses of data to become insight-driven, it’s advantageous to connect data from sales, product, and customer service departments for example, to help create a 360-degree picture that informs the next best conversation or action, and consequently creates long-term loyalty. Quality still applies but breaking down silos generates even more informative insights to support impactful marketing strategies and return on investment.

Equally important is inspiring a company-wide, insight-driven culture. When all teams are encouraged to use and share data effectively – led by example from the leadership team – insight becomes the foundation for decision-making in all business operations.

Myth #5: Data science is meant for large organisations

The allegedly hefty price tag attached to data science has led to the misguided belief that it can only be used by established businesses with deep pockets. In reality, it isn’t necessary to invest a small fortune in an in-house analytics infrastructure when there are SaaS (software as a service) companies with teams of experts and first-class technology, or open-source tools that can help process data at scale. Instead, recognising skills gaps within teams and offering tailored training is crucial to equip departments with the expertise to extract maximum value from data – whether it’s using in-house tech tools, open source or through SaaS companies. Even smaller organisations can access and leverage the benefits of data-driven insights with the right people onboard.

Myth #6: Data-driven decisions are enough for great marketing

Finally, businesses can view ‘data-driven’ as a fixed objective rather than an ongoing effort. While it’s true that accurate data will enable stronger decision making – and can instantly improve marketing strategies – many companies mistakenly view this as their final goal.

Instead, maintaining effective, insight-driven marketing requires long-term commitment. The dynamic nature of the industry and evolving consumer demands prove that business needs can change almost overnight. To be able to respond quickly, companies must always be open to exploring new methods and applications for their insights: the hallmark of agility.

There is no disputing data’s ability to open new opportunities for marketers but recognising the misconceptions and addressing them head on is a good starting point. All organisations, regardless of size, can achieve insight-driven success by evolving at the pace that is tailored to them, their team, and their commercial goals.

By valuing talent, prioritising data, and encouraging teams to view insight-driven operations as a continuous journey, businesses can take significant steps along the path to data maturity.

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