Consumers expect rich data and images to make purchase choices; business users need easy access to analytical data to make mission-critical decisions. These increasing demands for information are driving a need for improved product data availability and accuracy. And this is changing the way businesses go to market.
A staggering number of bricks and mortar and manufacturers are reforming their models to respond to this challenge. The direct-to-consumer (DTC) model, while not new, is becoming the centre stage to address these challenges. The optimal DTC model will vary depending on specific and contextual business objectives. However, there are many strategic benefits to going direct, but the main objectives include growing sales, gaining control over pricing, strengthening the brand, getting closer to consumers, and testing out new products and markets.
It is my contention that while the DTC model is gaining the deserved attention, much is to be done. In fact, among many challenges that this model poses, one in particular is largely overlooked vis-à-vis the processes and activities associated with sourcing product information from various providers, enriching product data to drive more sales and lower returns, and managing increasing product assortments across all channels. More precisely, the challenges that need to be overcome are better exemplified by the following points:
- Products have several variations to support different segments, markets, and campaigns
- Product components, ingredients, care information, environmental impact data and other facets of importance to the customer
- People are visual. This is why easy navigation around the website is vital. Having eye-catching images of your products or services (perhaps as they’re being performed or displayed as intended) is an effective way to visually communicate information to your customers and make it easier for them to evaluate options. If information and pictures are readily accessible then customers are more likely to purchase your products or services
- Rating, review and social data, stored within the product’s record rather than in separate systems
- Purchasing and sales measurements, for example, sales in-store, return rates, sales velocity, product views online, viewing and purchasing correlations) are often held across several systems, but increasingly this information is needed for search and recommendation.
The importance of product data and its use, combined with the increased demands on business as a result of inefficient, non-scaling approaches to data management today, provide an imperative to considering a PIM to ‘power’ cross-channel retail. Once established, PIM users repeatedly report higher ROI. It is also likely that we’ll see that PIM systems will rank alongside CRM, ERP, CMS, order management and merchandising systems as the pillars of cross-channel retailing at scale.
For all these reasons, choosing the right PIM strategy (and partner) is now a key decision. Get this decision wrong and it could become an expensive mistake.