How to Improve Cost-Efficient Business Decisions with Product Data
An undeniable part of working in business management is making strategic decisions. A poor decision could cost the business revenue and even cost employees their jobs. The brand image is at stake, too, with huge potential for upsetting customers and earning a bad reputation.
Business leaders have to look for opportunities to minimize costs and maximize revenue. These are the only two ways to improve cost efficient business. It's not as easy, though, as slashing costs in one place or finding new revenue in another. Strategic decisions can’t come at the cost of product quality or business practices.
Enter product data.
Most of today's biggest opportunities to improve cost efficient business strategies are backed by product data. That data includes all the product descriptions, user guides, and project imagery stored for each marketing and sales channel. No well-meaning strategy to make a business cost efficient will work if it’s planted in a product data desert.
Look at these principal opportunities for brand manufacturers to improve cost efficient business practices today. Then, learn how product data lays the groundwork for each.
Personalization and Email Content
Consumers today want to feel understood. Specifically, they expect personalization in their e-commerce experience before and after they buy. Especially after, and especially in email.
McKinsey studies have found that 71% of consumers expect companies (including yours) to deliver personalized interactions, and 76% of consumers feel frustrated when that doesn't happen.
Personalization is not just what consumers want, it also drives better business performance. The fastest-growing segment of companies today gets 40% more of their revenue from personalization efforts than the bottom 75%.
The top personalizations that customers expect are delivered in email marketing and include:
- Product recommendations relevant to each consumer
- Messaging tailored to each consumer's needs
- Offers specific to each consumer’s interests
Personalization email campaigns can be built with extraordinary segmentation. Customers who buy product X are probably in the market for product Y in a month or a refill of X in two. Customers who buy product Z would love to see more real-life applications of their product post-delivery.
The opportunities are endless, but they're all product-centric, and product data must be organized to support them. Otherwise, this great idea becomes a time suck, a money suck, and it won't even work.
Personalizations are based on automation in email, text, and ad campaigns. The products brands show their customers are based on recent purchases or interests. Product data supports this because each product in a catalog can be tagged and sorted in a product information management (PIM) software. When product information is stored in one repository where an attribute like "great cross-sell for product X" can be added, then personalization in its most cost-effective state is possible.
Data-driven decision-making can be done in the world of personalization once product data is updated with these attributes, too. How many cross-sale products are there for product X? A brand can filter real-time, living product data and find out which segments of customers need their own devoted personalization campaign.
Coupons or Discounts
More than 92% of consumers used coupons in the U.S. when making a purchase in 2020. With online shopping becoming the norm for more consumers and classes of products, it's easier for brands to promote deals and get them in front of consumers at the time of purchase.
Truly, every moment of the day is a time of purchase now with smartphone use up to almost 5 hours a day (one-third of consumers' waking hours).
Offering discounts includes loyalty program strategies and other promotional marketing. A brand can improve cost efficient business by catapulting revenue with these initiatives.
Product data stored in one central repository informs data-driven decision-making related to discounts and coupons. A brand can sort products based on what stock needs to move. It can sort products based on custom attributes built into catalog data like the cost of each product or the production time. Whatever discount strategy a brand uses to decide what offers to roll out, product data can be easily filtered to see what products are on the table for consideration.
A 2012 study showed that consumers who received a $10 voucher experienced a 38% spike in oxytocin levels. A brand’s management team can get the same high and improve cost efficient business with product data supporting their discount strategies.
For more ideas about discounts to offer, check out these coupon and loyalty strategies.
Social Media and Blogs
It's not automatically cost efficient to be on social media. In fact, it can suck money out of a brand just like a bear sucks honey out of a beehive, with just as much risk of getting stung.
It is automatically cost-inefficient not to be on social media, though. There are now more than 4.2 billion active users on social media. That’s twice as many as there were five years ago. Adult consumers spend an average of two and a half hours daily on social channels alone.
Whether product-related content is shared on page profiles, ads, or both, the first step is to build a product experience on those social channels. Users with certain interests need to see compelling ad content that feels personalized. It's exciting for them when their interest is piqued with a product they could use.
Once they click on any product content, the product pages on the other side have to feel like the same brand, the same voice, and represent the same product benefits. This kind of branding consistency is managed within product catalog data, specifically on a next-gen PIM. This advanced product catalog software is where all product data is pooled, including product images and video.
Most of the inefficiencies, when brands try to manage social media profiles, come down to product imagery. More versions of product content are created for each social channel with their unique dimensions and optimizations. That product imagery gets lost or duplicated in a labyrinth of shared folders. The wrong versions get edited or loaded. More ambitious and data-driven decision-making around social media is made when product data provides that fertile ground to plant big ideas.
Keep reading for more ideas on how to use product data on social media.
Partnerships That Make Sense
Brand manufacturers have explored many new partnerships in the digital space. There are new channels to sell on, new brands to share marketing with, and new shipping experiences to offer.
Managing partnerships as a nex-gen brand manufacturer requires managing product data in a way that it can be shared with the right partners at the right time and in the right format. There shouldn't be any more data shared than what the partner needs, and certainly no less. The product data also has to be totally accurate, complete, and up-to-date.
Brands that use a next-gen PIM have customizable attributes and easy channel management to devote to individual partners. Consider any partner a new "channel," and a brand can improve cost efficient business practices across internal practices and external business partnerships alike.
Marketing and branding efforts are inherently expensive. Scaling has costs upfront, and bringing on a business partner can open a world of rising costs above budget because of the growing number of factors a brand no longer has control over. Product data stored in a flexible, living repository supports data-driven decision-making for brands that explore any kind of partnership.
And more delegating for everything else!
Data-driven decision-making is at the heart of a brand's efforts to improve cost efficient business. Data does not always come in the form of performance metrics. Product data is the kind of data that serves as fertile ground to grow big ideas. And while marketing ideas get a lot of clout, most of the opportunities to improve cost efficient business is seen internally. Internal business practices can always use improvements. Maybe it's the introduction of software. Maybe it's the triage of people responsible for a task.
Collaboration is an inherent requirement for brand manufacturers because multiple departments play essential roles in creating products. From product development to marketing to logistics and even the customer service department, everyone needs their hands in product data if it's going to serve as the terra firma for all the other ideas described above.
Access to product data can be controlled user-by-user and permission-by-permission in the next-gen PIM. Just like the company Sherrill Furniture revealed in a case study by Amber Engine, a "mature" data process captures product data in each department as that data is created. The client was quoted saying, “We have 90% of the data we need through our [go-to-market] process now, and it’s all centralized, so it’s easier to find.”
With collaborations inside the brand and out, it's inevitable that some projects and tasks will go over time, over scope, or over budget. Brands improve cost efficient business with clean, consistent, and complete product data pooled in a living catalog because product data fuels everything a product-based business does.
Sometimes, data-driven decision-making points at "big idea" initiatives that simply aren't working, and they get dumped. However, most of these ideas just need to be planted in better soil and then cultivated with better product data.