Have you decided that it’s time to take your analytics capabilities to the next level? Maybe your IT team is spending too much time developing custom reports or supporting an outdated system. Perhaps you’re struggling to see the big picture of your enterprise across all channels. Whatever the driving force behind your decision to implement a new retail analytics solution, it’s important to plan wisely to mitigate the risks associated with implementing a new retail analytics solution. Here are some of the top challenges retailers must overcome when implementing analytics solutions.

Limitations in Data Availability

We live in an age of abundant data. Digital commerce has delivered a wealth of new data points about shoppers’ online buying and browsing personas. These massive amounts of data have the potential to translate into potentially lucrative insights for retailers. In reality, many retailers nowadays feel overwhelmed with information that’s not actually usable. Much of the data is unstructured, and spread across various systems, in different formats. When selecting and implementing an analytics solution for retail, it’s critical to first take a look at what data is available, from where, and in what format, to best understand how it can be channeled into reports and dashboards that deliver a holistic view of the enterprise.

Poor Data Quality

If the source data is of poor quality, then your reports and dashboards will fail to be useful. For instance, many retailers ask for shopper’s zip codes at the POS, but very often, cashiers looking for shortcuts will enter their own zip code over and over, rendering the data useless. Another example is retailers who struggle to connect the shopper’s profile across channels. It will be impossible to get an accurate picture of your top customers if you can’t tell that shopper X in store and shopper Y online are in fact the same person. It may be worthwhile to consider investing in data quality services in preparation for implementing a new retail analytics solution.

Weak User Adoption

Any retail system is only ever as good as its users. If your users don’t adopt the new retail analytics system as a tool they enjoy working with, then you won’t ever gain your full return on investment. Ensuring adequate training is a key part of change management. Training needs to continue after the onboarding phase. After working with the system for awhile, users will benefit from refresher training to learn how to do more with the system. Whereas a new user might rely on standard reports and dashboards, a more experienced user may be ready to make their own custom views. In addition to teaching users how to make the most of their new tool, taking the steps to ensure data quality is essential, because if users can’t trust the data they see in reports, then they will fail to fully adopt the new system.

Reports and Dashboards Misaligned with Overall Corporate Objectives

A new analytics tool can be exciting and at the same time, overwhelming. There is so much data to review that it can be easy to lose sight of what’s really important. Aligning reports and dashboards with overall corporate objectives is an important step to ensure that you gain the full benefits from the new system. Put the most important metrics up front and center so that users will naturally focus on what’s most important for the business. This may mean that your leadership team needs to invest some time in some visioning sessions before implementing the new analytics solution to ensure that there is strategic alignment among all stakeholders.

Losing Sight of the End Goal

As with many new tools, modern retail analytics solutions offer many exciting visualization, analysis, and predictive capabilities. There are lots of features to discover, and it can be a challenge to assess which ones are most important for your business, and which ones are just a distraction. Not every feature, report, or visualization is needed for every business. Keep your focus on your end goals, and remember that the analytics solution is a tool to propel you in that direction. If a feature isn’t helpful in that regard, then move on, and stay laser-focused on what really matters to your business.

Poor Performance

Massive amounts of data and modern visualization and manipulation capabilities demand a lot of server resources. Slow system performance will certainly impact the usefulness of the system and user adoption levels. Relying on a vendor that offers cloud services designed with the needs of retail analytics in mind is a great way to ensure fast performance while also reducing total cost of ownership, benefitting from a predictable cost structure, and reduced capital expenses.