top of page
  • Writer's pictureGraas

Challenges with siloed eCommerce data, and how to solve them

Updated: 8 hours ago


ecommerce and data analytics

For many eCommerce brands, gathering and processing data is a double-edged sword - there’s data coming in from multiple channels even as teams struggle to make sense of it. The same metrics that are vital for understanding the business can also become a burden when there is lack of true visibility between what happens across these data sources.


How can you break the data silos that are inherent to growth and use the information to your advantage?


The answer and the solution to your data woes lie in the ways data is handled at your end. Handling data as an eCommerce brand has to be done with precision and efficiency. You may have all the relevant data stored in your repository, however, it is of no use if you do not have the appropriate tools to combine and analyze them.


When relevant data points are not integrated, data becomes a challenge instead of being the insightful tool it should be. Silos can happen when data is spread across different departments or groups and they do not share a common platform.

Data silos can lead to a whole host of problems, but they can be summed up into two key challenges:

  • No single source of truth

  • Poor customer experience


Let’s dive into each of these and see how we can unravel the threads:


1. Making sense of eCommerce data and taking action


Understanding what is happening at the point of sale and everything leading up to this point is significant. Even the simplest of triggers, like seeing too many products out of stock, can cause customers to turn to a different brand. Why, then, do so many brands keep running out of stock anyway?


This is just one example of how some of the best-laid plans around data management go awry in eCommerce.


Most tools and platforms allow for some amount of data to be gathered but don’t tell us what to do with all of these numbers once they’re available. Case in point- it can be argued that email marketing tools offer insight into email open rates and therefore we think they are important, but experience tells us that just the act of opening an email means nothing.


Today, we cannot afford to have data that is essentially meaningless- everyone has access to the same numbers, so how can we do better?


Solving the problem at its root


The key to handling data better and removing silos is to begin with the end in mind. What end-goal are we hoping to achieve as a business outcome? How can we backward integrate the tactics needed to achieve this outcome? And where does data play a role in all of this?


Thinking of data this way ensures that it is gathered and handled in a more streamlined manner with clear positive impact on the business. Moreover, when all of these moving parts are managed on one platform, brands benefit from better visibility into what is and isn’t working. Inventory management, customer relationships, and order fulfillment can all be streamlined through business-first thinking around data.


The Grass Predictive AI Engine gathers data from all of your sales channels, marketing channels, ERP, OMS, and logistics partners and uses these data points to give you highly accurate insights.


Now, you know exactly which marketing campaign brought in the most conversions last quarter. With this insight, you can optimize ad spending on other channels and campaigns. Meanwhile, the Engine has also given you visibility into which products are moving fastest, so you can plan inventory accordingly.


Imagine what it would be like to manage all of these insights on one dashboard- campaign information, storefront optimization, SKU updates, orders and fulfilment can all be tracked on a single platform with the Graas Predictive AI Engine. Having Graas in your corner is like having a highly skilled data scientist by your side at all times.


2. A Sub-par User Experience


In today’s competitive online space, a brand is defined by the user experience. Poor user experience can cause confusion and frustration and that ultimately makes a customer not want to buy from you, despite intensive marketing efforts.


eCommerce stores need to operate across several marketing and sales channels, from email marketing and social media to web stores, marketplaces, and more for sales.


Users, on the other hand, rarely behave in predictable ways- remembering an ad they saw just when it is time to make a purchase, or moving from one sales channel to another completely organically as they browse for a good deal.


As a result, brands have very little visibility into the actual user journey, and may thus end up optimizing campaigns that don’t need to be optimized, or running campaigns that have less-than-expected outcomes. At the same time, users feel the friction of a sub-par marketing and sales process, and may over time, move to other brands.


Solving the problem at its root


Collecting information about the specifics of various marketing initiatives through data integration can help you calculate the success of that campaign through the number of website visits, sales, or social media interactions. Likewise, having a clearer picture of analytics from all of your sales funnels is extremely important for the success and growth of your business.


How can you implement this? With AI and automation.


Instead of spending several hours digging through disjointed analytics reports, the Graas Predictive AI Engine can give you a singular, streamlined view of data. By understanding customer behavior patterns gathered through behavior across multiple sales channels, Graas allows you, the brand owner, to make highly data-driven decisions regarding everything from how your webstore should be designed and what your marketing messaging should be, to how your checkout flow can be improved, all with the end-user in mind.


The moment a customer experiences a seamless journey from the first touchpoint to the very last one, they build affinity towards the brand and can, over time, become loyal, repeat customers.


Every eCommerce brand has been in a situation where data isn't providing them promised benefits, and is instead leading to more confusion. The Graas Platform was built for unified views of data, with one aim in mind- to make decisions easier, faster, and based on logic and data alone.


It is time to help you move to a powerful predictive engine that always preempts the problem, and comes back to you with actionable insights.


The Graas Predictive Engine not only generates valuable insights for your eCommerce business, but also provides actionable recommendations. Execute them in real-time to mitigate risks and take advantage of growth opportunities.


So if you're ready to take your eCommerce business to the next level, it's time to harness the power of the Graas Predictive AI Engine to make informed decisions that optimize costs, improve revenue, and drive growth. Give it a try.


Comments


bottom of page