Sagence works with industry-leading retailers to create data-driven retail strategies that emphasize seamless, cross-channel consumer journeys. Through focusing on the consumer first, Sagence is enabling retailers to concentrate on key initiatives and opportunities designed to build market share and personalized consumer experiences.
The Consumer Shopping Journey
- Social media platforms will continue to dominate both the time spent on devices and the shopping inspiration stage of the journey.
- Social media players will break down the current commerce barriers of trustworthiness and account setup/ease and buy buttons (in all their forms) will come closer and closer to the inspiration stage, however, integration with a true shopping experience will still prove difficult.
- Buy buttons (in all their forms) will be brought closer and closer to the inspiration stage.
- Retailers will increasingly embrace curation to compete in the inspiration stage.
- Showrooming and pop-ups will take hold, existing brick and mortar retail capacity will transform into distribution capacity, and online players will continue to rollout physical spaces.
- In-store and near-store consumer engagement through IoT, beacons, apps, etc. will become table stakes as consumer expectations continue to rise.
- Metadata management and AI capabilities will become competitive advantages for retailers looking to attract consumers in the shopping stage (e.g., browse, research, and select).
- Traditional retailers will stop reporting e-commerce revenue growth as digital engagement across the journey increases.
- Check-in progress will help eliminate in-store checkout friction and will help alleviate the numerous and painful adoptions of new payment formats and technologies.
- Retailers will adopt to the customer trend for the Buy Online, Pick Up in Store (BOPIS) model through improving inventory management, while lowering retailer shipping costs.
- Fast in-store pickups and home deliveries will continue to make strides, requiring supply chain transformations and fueling further reductions in overall physical retail space.
- IoT will continue to help improve inventory tracking and merchandising, not only within the supply chain but within individual stores (e.g., endcap/promotion analysis).
- Greater consumer engagement and machine learning capabilities will enable more effective localization practices.
- Retailers and brands that promote and leverage post-purchase, user-generated content (UGC) will maintain a competitive advantage.
- As more and more products incorporate IoT platforms, retailers and brands will leverage the “conversations” to build competitive advantages (e.g., marketing campaigns and improvements in products and services).
Client Success Stories
Sagence designed a supply chain transformation framework, in the context of the retail industry, that enabled a big-box retailer to accelerate its transformation process while fostering innovation.
Sagence designed a marketplace strategy framework that enabled a leading, national big box retailer to effectively evaluate the addition of a marketplace product to their existing brick and mortar and e-commerce channels.
Sagence’s structured data profiling approach enabled a major online payment systems company to evaluate the customer data tracking capabilities of its legacy and new platforms yielding improved customer behavior insights.
Sagence’s innovation portfolio management expertise helped a software company generate trends in product usage data to better understand consumer behavior across its diverse user base.
A leading retailer was seeking innovative approaches to gain visibility and control over inventory within their supply chain.
Sagence implemented a marketing data warehouse that provided a nutritional supplements direct marketer much needed customer intelligence.
Sagence conducted an in-depth analysis of our client’s pricing practices and developed unique reporting views to guide future pricing activity.
Sagence used its expertise in machine learning and statistical analysis to develop models that determined the incremental value of a specific set of interactions with its customers.