PIM Is Business Critical Series: How the Volume, Velocity, and Veracity of Product Data Are Changing

Product data is changing. With pressures from outside and inside brands, what was once a design-centric set of product specifications in CAD has become a complex catalog of product data for multiple sales partners and sales channels. Each channel requires its own template of product attributes while the information customers expect has become greater.

Do your customers expect 3D renderings or "look inside" images or even AR experiences along with high-quality product photos?

Do your clients expect all the standard product size, weight, and material attributes plus information on the intended use, benefits, care guides, warranty information, and more?

With more competitive expectations of today’s product listings, product data is now the key asset in delighting consumers.

Internal Pressures Building Product Data

The need for product data has grown across departments within a brand. Product data has swollen even more as a result of new internal processes. What was once the sole domain of product development is now something marketing, customer service, web development, and other departments also contribute to.

How else would product data be prepared for all those new sales channels without other departments stepping in?

The nature of the combined internal and external pressures on product data has ballooned the operational costs of data management. As the volume of product data has grown, the velocity required to push new data to market has demanded managing more product data faster than ever. The veracity of data, too, is under accidental attack by the many departments with their hands in product data spreadsheets.

Can you feel the pressure building?

What does it all mean? Where's it all going?

Keep reading to learn about the changes in product data volume, velocity, and veracity, and what these changes mean for brands now and in the future.

The Volume of Product Data

In recent years, the volume of product data has changed in four ways:

1. New attribute fields are required for new sales channels and sellers
2. Different versions of the same attributes are required for each channel or seller
3. Different systems for naming and managing attributes across departments
4. The ever-growing number of SKUs

Product data today means much more than basic product measurements, colors, and materials. It includes a long list of enriched and essential product data that ropes product imagery and video into the mix.

The volume of product data for each brand will depend on how many new SKUs are added and how many sales channels or sellers they work with. Add to that the volume of data once it’s duplicated and managed differently by multiple internal departments, and the growth in volume is exponential.

For one example, think about a brand that has 50 new SKUs this year alone, added to an existing product catalog of 500 products. That 10% increase is then multiplied by the six sales channels or sellers that the brand works with. Then, multiply that by the number of spreadsheets of product data kept between departments.

The volume of product data easily just mushroomed to about 30 times its size.

The Velocity of Product Data

The velocity or speed of product data has become far more aggressive in recent years. By that, we mean that brands are required to make changes more often and launch product data to market faster. These rapid-fire changes are due to:

1. New sales channels or seller requirements
2. Updates to sales channels or seller requirements
3. New product collections or product updates to launch

Despite these requirements, the operational cost of managing product data has ballooned along with the time it takes brands to prepare that product data. Many clients of Amber Engine state that managing product information for just one SKU on one web-based platform can take 20-45 minutes, depending on how much of the data is already available and what updates need to be made.

The total time for most brands to prepare a new product launch totals several months.

Brands today aren't realistic when creating product launch timelines. The can of worms that awaits when the launch is announced is unfathomably deep. Marketing needs to dig into the CAD data of new SKUs, and the time for data collection, clean-up, and organization is always underestimated.

Just look at this client who spent months preparing new products for launch before. With the implementation of the Amber Engine PIM (product information management) software, that time was reduced to a couple of hours. This next-generation standard for data velocity is the only path forward for brand manufacturers to reduce the operational cost of product information management and keep up with the new demands of data speed.

The Veracity of Product Data

The veracity of product data refers to how accurate and complete it is. Incomplete product data can be misleading and will ultimately flatline sales because customers today expect a full suite of product information before making a purchase. Especially with other products on the same platform offering greater detail, a thin product listing will not invite consumer confidence.

The accuracy of product data has been tracked and managed manually by brands as long as the concept has existed. With the growing volume and velocity of product data, however, manual systems are unsustainable. The level of human error and the finite resources of time and energy have deteriorated the quality of product data as the volume and velocity have bloated.

Fortunately, PIM software was designed to make correcting and completing product data a fast, simple, and foolproof process. The next-gen PIM has built-in product data quality scoring so brands can instantly filter the products that are missing key attributes or whose data doesn't fit the format required.

Filtering and sorting data by quality score makes versioning product data for the long list of sellers and sales channels faster.

The next-gen PIM even streamlines users updating low-scoring product data in bulk. With this ability in a brand’s quiver, the operational cost of scrubbing product data clean has never been so quickly reduced after decades of its steady rise.

The Burden of Using Product Data Everywhere: Do you have an option?

The volume of product data has grown as a product of the era of e-commerce. Direct-to-consumer and business-to-business brands alike have pressure from internal and external sources to increase the volume of product data to convince customers to buy.

These same digital channels require the velocity of product data updates to come down to a fraction of what it was before. If a brand isn't ready "yesterday," it will be left in the dust.

This changing landscape has also strained the veracity of product data, especially as more departments within brands get involved in managing data. If the marketing department lists one key attribute differently than customer service does, or if product development doesn't harvest all the attributes it possibly can from CAD, then brands are stuck with dirty data that takes months to clean up.

The operational cost of managing product data is the first consideration for most brands, but the opportunity cost is even greater. These shifts in product data absolutely reduce revenue and, consequently, the bottom line if brands aren't using product data wisely.

A brand today is only left with the option to adapt, or to otherwise take on colossal (and fast-growing) operational costs while sacrificing a growing stream of revenue.

The next-gen PIM technology came to the rescue for both customer-facing data and internal collaboration within brands. The PIM market is slated to grow about 75% from its numbers in 2020 and the year 2026 due to the benefits it’s provided brands. Product data management requirements will continue evolving, too, and PIM technology is central in preparing for what’s next.

Keep reading to learn more about how to future-proof your brand.