How to Manage eCommerce Orders for Good Analysis and Insights

A warehouse full of workstations and shelves.

Good data is at the core of business forecasting. The ability to generate high quality, detailed reports is paramount for informed decision-making. Accurate reporting not only aids in evaluating current performance, but also in forecasting future trends, optimising operational efficiency, and ensuring regulatory compliance. 

For businesses using enterprise resource planning (ERP) and accounting systems, such as Unleashed and Xero, both powerful tools in the realms of inventory management and accounting respectively, segmenting data effectively is crucial to maximising the effectiveness of reports. By combining these systems, businesses can unlock a wealth of insights, enabling the creation of detailed reports that cover various aspects of operations, from inventory turnover rates and cost of goods sold (CoGS) to sales performance and financial health metrics. 

Increasingly, AI (Artificial Intelligence) systems are being used in business data analysis. Such AI systems, like any other system, depend on high quality data in order to produce good, reliable outputs. Any analysis is only as good as the data it is using, so it stands to reason that business data for online retailers needs to be handled well, ensuring reports and forecasts generated downstream can offer insights that decision makers can reliably leverage.

Conversely, generic, uncategorised sales data is never going to provide valuable insights into the performance of different sales channels, market regions, currencies, payment types (the list goes on…).  It is critically important to make sure that your order and stock management is intelligently filtering and sorting your orders by the criteria that you wish to report on. With a rock-solid order management foundation, the quality of the reports and insights you derive from it will match that quality. 

How does AI help make business decisions?

Anticipating market changes is a crucial aspect of maintaining a competitive edge and ensuring the long-term success of a business. Decision makers must understand the past and present of their business health in order to forecast the future. By making use of platforms that integrate artificial intelligence (AI), such as Tableau, IBM Cognos, or Google’s own Looker, along with detailed and granular categorisation in Unleashed and Xero, you can better position your company to anticipate and respond to market shifts. AIs, compared to conventional systems, have a greater ability to detect hidden patterns within data. On top of that, AIs that make use of Large Language Models (LLMs) can better “understand” non-numerical information, and also help the retailer to interpret their data, by offering explanations in a conversational style. Here are some key areas that an AI can help retailers with:

Monitoring Key Performance Indicators (KPIs)

AI tools can continuously monitor specific KPIs, such as sales growth rates, customer acquisition costs, and inventory turnover ratios, providing early warning signs of market changes. AI can alert you to sudden declines in sales growth, indicating shifting consumer preferences or emerging competitive threats, allowing for timely strategic adjustments.

Analysing Historical Data & Forecasting Financial Health

AI-driven reporting allows for in-depth analysis of historical sales data, inventory turnover, and financial performance. With AI, one can identify patterns, even subtle patterns, over time that may indicate upcoming market changes. With accurate and detailed financial reports from Unleashed or Xero, AI can perform robust financial forecasting. AI models can project future revenue, expenses, and cash flows based on historical data. Being financially prepared through AI-driven forecasts allows you to invest in opportunities or weather downturns more effectively.

Identifying Seasonal Trends

AI can automatically categorise order data to uncover seasonal trends, be that Summer versus Winter, or how each fiscal quarte; and with data covering multiple years, cyclical trends may emerge. Understanding these trends through analysis enables you to prepare for peak seasons, manage inventory levels efficiently, and adjust marketing strategies accordingly. Predictive analytics can forecast seasonal demand spikes, ensuring optimal stock levels.

Understanding Regional Market Trends

From the temporal to the spatial, it is also important to understand regional trends. With geographically categorised order management, the stage is set for regional performance to be analysed and market trends forecasted! With an ordered and granular data set, AI can identify trends in different areas, enabling tailored marketing and sales strategies for each region.

Additionally, individual product performance can be broken down by region, allowing for the prediction of  regional demand variations, ensuring optimal inventory distribution and reducing stock outs and overstock situations. This information is crucial to be able to pinpoint underperforming regions, uncovering opportunities for market expansion or strategic adjustments.

But how can one prepare their business so that it’s ready for deep analysis? The first step is intelligent order management.

How to automatically categorise orders in Unleashed

When integrating an eCommerce platform like Shopify with Unleashed, there are likely to be multiple sales channels. Even with just one single integrated Shopify store, a seller’s list of channels could include:

  • Direct-to-Customer (DTC)
  • Business-to-Business (B2B)
  • Shopify POS
  • Integrated Marketplace Orders (Amazon)
  • Integrated Marketplace Orders (Walmart)
  • Integrated Dropshipping Orders
  • Preorders

When syncing these orders with other platforms, the question is: how can one identify them? Unleashed offers several ways to achieve this visibility, but the two key (and searchable) fields are sales order groups and customer accounts. 

Sales Order Groups

Sales order groups are just that, a method of grouping or categorising orders by any user-defined criteria. The number of sales order groups one can make is essentially unlimited, and so one is free to create as many groups as necessary to achieve the granularity they require. Sales channels can be categorised relatively broadly, such as with a single group for each sale type:

  1. Shopify DTC
  2. Shopify B2B
  3. Walmart
    Etc…

Geographical region is also a powerful metric to identify. Using order shipping or billing address, orders can be grouped as such. For example:

  1. United Kingdom
  2. Europe
  3. USA
  4. Rest of World

Moreover, one could subdivide their categories, combining both of the above to achieve finer granularity:

  1. Shopify DTC UK
  2. Shopify DTC Europe
  3. Shopify DTC Rest of World
  4. Shopify B2B UK
  5. Shopify B2B Europe
    Etc…

On top of channel and region, or the many other metrics one may wish to track, it’s likely that one may also wish to report on what currencies perform best for each sales channel; Unleashed’s customer accounts are the best way to achieve this.

Customer Accounts

Unleashed customer accounts are another great method of categorising orders that can be used in addition to sales order groups. However, making use of customer accounts for reporting comes with the caveat that sellers will disable the collection of individual customer accounts in Unleashed, and instead shifting to using fewer, user-defined accounts. In other words, your Unleashed customer records would need to be set up not as individual customer accounts, such as “Harry Perkin”, but as dedicated records that correspond to that sales channel. 

Unleashed customers can use a single currency each, so using them to report on currency is a natural fit. Let’s use our Shopify sales channels again as an example. Independent of the sales order group, orders can be assigned a predefined customer depending on the currency of that order.

As with order groups, customer accounts can be assigned with relatively broad criteria, such as to report on the sales by currency for a single Shopify store:

  • £ GBP -> Shopify GBP Customer
  • $ USD -> Shopify USD Customer
  • € EUR -> Shopify EUR Customer

Or, again, we can subdivide our concerns, such as by the different order types from within a Shopify store:

  • Shopify DTC orders in GBP -> DTC GBP Customer
  • Shopify DTC orders in USD -> DTC USD Customer
  • Dropship Orders in GBP -> Dropship GBP Customer
  • Dropship Orders in EUR -> Dropship EUR Customer
    Etc…

So, using customer accounts in tandem with sales order groups is a powerful way to achieve intelligent sorting of sales channels, at any level of granularity that you wish to achieve. With an automation tool like TIDE, order properties, like currency, delivery address, or payment type, can be identified, meaning that orders can be dynamically sorted into any number of user-defined segments, enabling complex order management without the need for any manual intervention. 

What’s more, when integrating Unleashed with Xero, Xero will inherit the categorisation you have already established in Unleashed, thus seamlessly continuing the chain of high-quality data. From this solid foundation, your data can be fed into reporting tools that may leverage machine learning and AI to generate powerful business insights.

Summary

Whether with Unleashed, Xero, Lightspeed, Netsuite, or beyond, it’s clear that the generation of good data begins with good order management; and good order management requires good automation. With TIDE, sellers are provided a powerful, flexible integration and automation tool that helps them achieve this. Beyond simply syncing business data between platforms, TIDE will also query your data, apply conditional logic, and assign orders to user-defined categories and dedicated sales accounts, fully automating complex order management. This achieves two key things:

  1. The burden of manual order management is eliminated. TIDE agents work with sellers to create complex automation solutions, removing the need for tedious and costly manual work.
  2. Your orders and primed for deep reporting and analytics. With granular categorisation, based on metrics that are important to you, the quality of your data is increased tremendously. With a quality input, you can be confident in the insights offered by analytical and forecasting reports generated by AI or conventional programs.

Sellers can rest easy in the knowledge that expensive work hours are saved, and future financial decisions are made based on solid foundations.

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