Three strategies that can ensure product data is accurate and up to date for retailers and brands selling on their own websites and online marketplaces.

Abnesh Raina, founder and CEO, PlumSlice Labs

Abnesh Raina, founder and CEO, PlumSlice Labs

Today’s complex multichannel commerce environment means brands have to be more aggressive about rolling out more products across multiple owned and third-party channels. Yet the requirements of an omnichannel environment, including in-store, e-commerce and marketplace platforms like Amazon, have changed. And with that, the fundamental requirements to ensure each product enters the right channel at the right time, with the right information, are increasingly complex.

The challenge of multichannel retailing deepens even further since getting products to market leads to a decentralized ecosystem, often made up of 10-15 disparate internal teams working independently, plus vendors and suppliers. As even more channels and teams are integrated, brands and retailers need a strategy that not only automates how they manage these increasingly complex workflows, but ensures data accuracy for each and every product in each and every channel.

Technology aside, the proper processes must be in place to ensure an effective multichannel retailing strategy. Therefore, retailers should consider the following key three factors to create a successful multichannel strategy:

Establish a digital data team

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Retailers large and small are continuing their digital expansion, and this involves either expanding their own digital properties and complementing them with third-party marketplaces, or solely relying on the latter as their main form of digital presence. To succeed, retailers and brands must implement a flexible process where they can provide accurate product information, as well as leverage virtual SKUs across their partner network, with dropship and endless aisle capabilities.

A combination of human and machine-driven processes is the key to nimble and swift expansion.

People and data are the keys to this flexibility. In order to effectively scale, retailers should designate a digital data analytics team or a chief digital officer who is in charge of reviewing the data required for each touchpoint. This will help ensure accuracy and an improved experience for consumers. As we already know, today’s retailers are overwhelmed with the amount of data they must review. And while they can utilize technology to aid this process, a combination of human and machine-driven processes is the key to nimble and swift expansion.

Automate data governance

Once a digital team is established, a set of key data rules for each channel will need to be formulated to not only create speed-to-market throughout owned and third-party channels but to also allow product accuracy and brand integrity as organizations continue to scale digitally. Automating data governance can be a big aid to ensuring the right information is in the right place at the right time, and that the data ultimately leads to product purchases. However, the digital team needs to establish proper data governance or rules beforehand to deliver accurate information and not waste cycles on iteration and mending product data.

Create contingent workflows with machine learning

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The retail industry is in a continuous state of flux, and as such, retailer workflows are also ever-changing. When it comes to digital scalability, retailers should create a dynamic workflow process that accounts for unforeseen or last-minute changes. This is where machine learning comes into play.

After data governance is established, working with a technology provider to create a series of algorithms that accounts for new scenarios will help create a multidimensional environment in which retailers can quickly update information and make the necessary changes to provide the most accurate product information to date, adhere to customer expectations and ultimately make the sale.

To create an effective strategy for contingent workflows, retailers need to work with their partners to develop a series of flexible algorithms that enable planning, cleaning, analysis and final product data presentation for all scenarios. Through a flexible machine learning environment, retailers will be able to create a concrete process that accounts for data replication and multidimensionality in an environment that is always changing. Ultimately, this creates better accuracy, efficiency and standardization so that retailers can quickly scale the business.

Every day we hear about the launch of new technologies promising to take a retail organization to the next level. While there is truth in the fact that technology is a vital resource in all retailers’ portfolios, when it comes to digital scalability for multichannel retailing, retailers need to prioritize processes first. Only when these are in place does engaging with a technology provider to complete their multichannel retailing strategy make sense.

PlumSlice Labs provides cloud-based product information management technology for retailers and distributors.

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