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With data being generated at an unimaginable pace – by devices, customers, social media interactions, and more – relying on gut or intuition to make business decisions is a recipe for disaster. Despite that pressure, and a commitment, to embrace modern analytics, the opportunity to leverage data remains largely untapped.

Inconsistency in data quality, siloed systems and departments, and the absence of the right tools often erode trust and compel decision-makers to favor tradition, norms, and intuition over insight. Most B2B marketers are also unable to prove the value of analytics to the C-suite – which further dampens adoption.

Why analytics initiatives fall flat

Although B2B companies around the world understand the impact analytics can have on their business performance, many struggle to meaningfully adopt analytics-driven strategies. Despite access to sophisticated enterprise software systems and analytics and BI tools, they struggle to apply data-driven insights to their business strategies and campaigns. And in reality, it’s not the volume of data that’s the problem; it’s how scattered data is across numerous systems that prevents it from giving value.

Here are some reasons why analytics initiatives for B2B companies don’t deliver the desired results:

  1. Not sure how to apply analytics: Although several B2B companies have started investing in advanced BI tools to unearth insight into their supply chains, sales, customers and markets, they hit a roadblock in applying the results of these tools in their day-to-day operations. Typical analytics and business intelligence tools merely collect a ton of data and report on it. They don’t give decision-makers the ability to take timely action. In the end, a spreadsheet full of data means nothing if companies cannot tie the information from multiple sources together, tell a story, give it meaning, and make it actionable.
  2. “Fear of analytics” jargon: When it comes to analytics, in traditional sectors like manufacturing, there is also a common “fear” or suspicion. Some of that is down to the fancy tech jargon that is commonly associated with analytics. The intent, process, and, even, outcomes are couched in jargon that many of the experts in these businesses do not relate to. For instance, in the manufacturing space, automation and robotization has often been associated with jobs becoming redundant. This results in users becoming anxious about the analytics initiatives. In that context, analytics being set forth as some sort of arcane knowledge in unrelatable terms makes it hard to accept. If analytics is not made approachable and accessible, not only are the outcomes unlikely but organizations could struggle with getting projects off the ground.
  3. Solving the wrong problem: Many B2B companies fail to clearly define their analytics needs accurately which makes for a rocky start. Applying analytics across the enterprise and expecting miraculous results is a battle lost before it begins. Unless companies understand the problem they are trying to solve or the processes they must prioritize for transformation, they will not be able to identify issues that are real, measurable, and solvable.
  4. Operating in fire-fighting mode: B2B companies often get crushed under the massive volume of data. This is why, they often function in a very reactive manner, responding to events that have already occurred. Such an approach restricts them from taking proactive actions while impacting their ability to understand what buyers are likely to do in the future – based on their current and past behaviors.
  5. Analyzing only past data: A lot of B2B companies also use modern analytical tools only to carry out a historical analysis of their marketing campaigns, customer behavior, product response, etc. Such analytics can only report on things that have happened in the past, and although that is valuable, it doesn’t tell them what could happen in the future. With no information on what product information customers might seek in the future or how market dynamics can change, companies struggle to personalize interactions, design product content and drive campaigns.
  6. Lack of the right resources: Many B2B organizations have the money to invest in modern analytical tools but not the tech resources who know how to use these tools and apply their results to improve business outcomes. In the absence of the right resources, companies struggle to derive insightful recommendations that could deliver value from their analytics investments. Such companies also hit a roadblock when they face an issue with their BI tool – not knowing what went wrong or how to solve it.
  7. No process in place to measure efforts: Metrics are critical to any business activity. With analytics becoming such an integral aspect of successful businesses, it is imperative that B2B companies have the processes in place to track and measure the progress of their analytics efforts. Without that, it becomes nearly impossible for companies to understand what’s working and what’s not. Companies that fail to evaluate the impact of their analytics efforts are often the ones that fail at proving the ROI – which could bring the entire initiative down.

The business benefits of analytics

Clearly, it is not uncommon for B2B companies to fail at their analytics efforts. The good thing is, there are a lot of quantifiable benefits that analytics can help organizations achieve. This makes the attempt worthwhile. Analytics can enable organizations define clear goals, drive more conversion ROI, and improve the customer experience. Analytics can help you:

  • Improve operational efficiency: When you begin understanding the goals of your business and how (and where) you think you can apply analytics, you can improve the outcomes of your day-to-day operations.
  • Drive measurable results: Once you can define the questions you want to be answered with the data you collect, you will be able to apply relevant data into your analytics algorithms and arrive at the right answers.
  • Connect insights with strategy: With the right people on board who can demonstrate the value of your analytics programs to your C-suite, you can leverage their deep technical knowledge to connect insights to strategy -directly.
  • Improve decision-making: When you invest in tools that are easy to implement and use, don’t need a lot of coding, are economical and match the skills of the analytics resources you have, you can automate workflows and leverage dynamic reports and dashboards for quick decision-making.
  • Monitor success (and failure); With analytics, you can identify and monitor a small set of important metrics that tie to business objectives and use the right technology to best measure those data points.

From providing targeted product information to precise demand forecasting, better inventory management to recommendation engines – the B2B sector is buzzing with innovation around machine learning and advanced analytics. While analytics isn’t a magic bullet, the trick is to embrace analytics in the manner most appropriate to your business. That is done, you may be able to deliver meaningful value to customers, open new sources of revenue, and boost growth.