3 Ways to Use Data to Drive New Product Development ‘Like a Boss’

3 Ways to Use Data to Drive New Product Development ‘Like a Boss’

So, you want to grow your retail business?

While there are many strategies toward achieving this goal, retail growth is about more than increasing sales and developing a presence on new channels. It could also include an expansion of your product offerings.

Whether you're adding to an existing product line or developing a new item altogether, it can be difficult to decide on a design, set pricing, and anticipate demand.

Savvy retailers that leverage data trends and employ strong forecasting analytics can make more informed decisions regarding product development, and use these new offerings to reach their growth goals.

Let’s discuss their approach so you can compete at their level.

1. Trend Tracking to Inform Development

Tracking larger trends, rather than relying solely on your own data can be most helpful in informing product development.

Whenever Apple comes out with a new iPhone, accessories brands are quick to come out with phone covers in dimensions sized to fit the latest model. Similarly, when the Fitbit became a fixture on seemingly everyone’s wrist, apparel and accessories designer Tory Burch partnered with Fitbit for a more subtle, elegant version of the health-monitoring bracelet.

Health monitoring bracelet

Image via Closet Confessional

Some entrepreneurial retailers have even created entire businesses out of anticipating customer needs and following trends.

Chaim Pikarski, the founder of C&A Marketing, built a team of people whose sole job was to read reviews on Amazon to determine where products are falling short and where there might be demand for an improved version.

What’s the benefit?

Scouring the web and accumulating data based on customer demand has enabled Pikarski to build a business that does nine-figures in sales annually and grows approximately 30% year over year.

While you may not choose to build an entire business based solely on customer reviews, C&A Marketing’s rapid growth proves that listening to prospective customers is a great place to start.

Assessing demand based on what customers are already requesting and tracking and aggregating this data will enable you to make informed decisions regarding product development, rather than following a hunch.

2. Let Data Drive Your Product Development Strategy

Tracking data trends to inform new product development is the most foolproof way to know you’re making products that will resonate with and excite your customers. But deciding what products to create is only half the battle.

Once a new product has been developed, it must be strategically positioned in the marketplace, priced for profitability, and properly stocked to support expected demand.

What’s in a Name?

At Stitch, we frequently analyze retail data in aggregate to uncover trends. Seemingly simplistic things like the color name you choose to describe a product can seriously impact sales.

For example, we found that red color families generate up to 28% higher revenue with standard names such as red, maroon, or crimson, versus creative equivalents, such as strawberry, raspberry or cherry. Because this classic color name performs better, businesses can save time and creative resources by sticking with tradition.

But the color-naming rule isn’t one-size-fits-all. Colors in the purple family generated up to 31% higher revenue when creatively named. Understanding the nuances of data across various products and variants is critical to making informed decisions and focusing your efforts appropriately.

Sales Forecasting Made Simple

Forecasting sales is an imprecise, but necessary, science for retailers. But it doesn’t need to require expensive software or dedicated full-time employees.

PricewaterhouseCoopers correlated quarterly Google Trends data with historical quarterly sales performance for a set of prominent retailers and brands and then compared it with a model based on that company’s own sales history.

In each instance, the Google Trends data significantly outperformed a model based on the retailer’s historical sales. In 75% of these testing scenarios, topline sales forecasts for test periods made with only a retailer’s Google Trend performance were more accurate than simple forecasts made with a retailer’s own sales history.

PWC chart

Image via PricewaterhouseCoopers

Sometimes just Googling your business is enough to provide you with the insight you need to make sure you’ll have what customers want, when they want it.

Strategic Pricing

While assessing competitors’ pricing is a great place to start, there is a lot more to the economics behind choosing the best price for your product and data can help you know where to start.  

Tools like Feedvisor allow you to enter your ceiling and floor prices and let their algorithm decide the pricing sweet spot for each of your products. Feedvisor uses Big Data from other retailers and their customers to make objective decisions while avoiding issues due to human error.

Don’t let customers scoff at your prices when there is data at your fingertips to ensure your pricing is not only strategic but also competitive and fair.

Take Advantage of Bundling

Bundling is a great way to introduce new products or teaser products to customers. To get started, leverage your historic sales data to identify best-sellers and complementary products. That way, you can get your new product into the hands of many customers by tying them to  complementary product types.

You can also clear out dead stock with bundling. To do this, pair a bestseller with stock that might be collecting dust and make room for fresh inventory. Or introduce customers to items they typically wouldn’t buy with interesting bundles that offer bestsellers paired with newer products.

Risk-averse? Try bundling products you’re already selling together, thus creating a “new” product. Bundling is one of the simplest, most low-risk ways to create a “new” product.

3. Implement a Feedback Loop

Once you’ve designed a well-researched product you’re excited about, it’s time to evaluate whether or not you’ve succeeded in delighting your customers.

By evaluating customer reviews when determining demand for new products, you can quickly gauge how customers are reacting to your newest offerings.

Amazon Kindle has  done this successfully; they went through thousands of customer reviews and continue to create new versions of the e-reader by incorporating the written  feedback into new product designs.

Not only does this approach help Amazon and other retailers create a product you know your customers want, but it shows them you are listening.

Kindle image

Social media can also provide customer-based data to inform new products. Subscription beauty brand Birchbox uses the popular photo-disappearing app, Snapchat to track their customers’ reactions to certain products. By encouraging customers to engage with the app by screenshotting certain products (the app tracks who takes a screenshot so this data then lives in Snapchat) or taking product pictures based on prompts, Birchbox is better able to understand which products resonate with their customer base.

Data can also inform your rate of sales and returns. How are your new products measuring up against items that have done well (or not so well) in the past? Historic data can help you determine your busiest seasons and bestsellers, better informing you of when you’re at risk of running out of certain products (we’ll be diving into how to access this in the final installment of our blog series).

The answer to this question will close the feedback loop as you fix or sunset a product that isn’t doing well, or think of ways to make a successful product even better with upgraded models or complementary items.

Data takes the guesswork out of running your business from customer experience to digital optimization to your product line allowing you to make more informed decisions. For more tips on making data work for your business, come back for the last installment of our series, in which we’ll discuss how you can use data to make operational improvements.


About The Author

Bridge Mellichamp is the Director of Data Science and Special Projects at Stitch Labs. Numbers excite her more than you can imagine; at the core, she’s driven by helping Stitch and its customers make sense of their data so they can make incredibly smart business decisions.