Data-driven product development

Product development drives business success. If you’re not always improving your business, then you risk falling behind your competitors. Still, it’s worth noting that when we say ‘product’ development, we don’t necessarily mean a physical product. It might be a new service to offer your customers. Or it might be something internal and not customer-facing at all. For example, a new business process or a system to streamline operations.

In that sense, a ‘product’ is also a kind of project. But while project management is its own, well-understood discipline, product development can be as structured, or as unstructured, as you like.

However, we think that, if you want to develop products efficiently and with a good success rate, then a data-based process is best. Intuition or ‘gut feel’ can be a great starting point, but data and analytics are critical. They can help ensure your ideas are viable and gauge the market’s likely response.

Internal data: Know what your customers want

It’s eye-opening to consider just how much data most businesses gather about their customers. As long as it’s collected, stored and secured appropriately, there’s no reason not to use customer data to help you determine what your customers want.

The most obvious source is purchase and sales data. What’s selling and what’s not? Are certain items or services often sold together, or in sequence? This information reveals where customers are willing to put their money and can identify gaps in purchasing patterns.

You can also look at support tickets as well as customer queries and complaints. How are customers using your products? Where are customers struggling? Is there a pattern of failures or customer difficulties? Are customers always asking for a new feature or product type? This kind of data can help you improve existing products as well as pointing the way to new offerings.

Accessing this information doesn’t need to be complicated. If you’ve got an enterprise resource planning (ERP) system, then it can become your primary data repository. Using your ERP like this makes it easier for your analytics engine to crunch the data and reveal insights that you might otherwise miss.

External data: Focus your organisation on customers

Product development also requires external data. That is, information that comes directly from your customers, not from your internal systems and sources.

Where possible, we recommend meeting and speaking with your customers. It can be handy to have a list of queries to raise with them. This list can be something like a customer satisfaction survey, but ideally, you’ll supplement it with an unstructured conversation.

This is a great way to learn about your customers’ workflows, work habits and any unmet needs. Ask them directly – what’s your biggest problem? What’s the one product (or service) you wish you had?

Such conversations can be a rich source of insights. Just remember to check your data to see if there’s anything actionable underlying it all.

It’s also critical to improve your business’s customer experience and user experience. Doing this will make it easier and more pleasant to interact with you. Set up systems (in person or online) to encourage constructive feedback and comments. Make sure that you respond to feedback and comments where possible.

Capture this unstructured data and convert it into structured data that you can properly analyse. You’ll now have a rich and unique source of insight. Again, your ERP system is a great place to store this data.

Combined data: Insights and product development

Here’s where the rubber meets the road: using your data-based insights to generate and evaluate product ideas. There are a few top-line things you can address to help make the process work effectively.

First, check your data. Are you gathering the right information? New data sources can lead to new insights, and further questions can yield new answers.

Second, refine your product development process. Make sure it’s consistent, so you’re gathering similar data sets for each product idea. It should also be rigorous and thorough, and efficient for you to access and administer.

Third, use analytics and machine learning to link sales success with different product types or attributes. For example, if you’re a fashion retailer, break your sales data down by styles, colours, materials and suppliers. This breakdown will tell you what your customers want.

Finally, and most importantly, solve problems, don’t sell products. Think beyond your current offerings and try to understand what your customers want – what problems or situations your products (and services) help them resolve or simplify.

If you can think of yourself not as a widget-seller, but rather as a problem-solver, then you’ll be helping your business to thrive and survive.


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