Monitoring growth initiatives by seeking to connect individual team objectives with overarching company goals, the intent is to provide enhanced e-commerce teams with real-time data and machine learning-driven insights. Executing company-wide agenda involves creating a “clear focus for teams and individuals” and hosting these goals in a seamless structure, said Kristen Luppino, people operations manager at floral subscription provider, UrbanStems and beta-tester of Yaguara.
Similar in manner to how fitness trackers shape workout recommendations and set goals for you, Yaguara intends to “define and assign quantifiable key results that teams should be working towards” in a framework catered to cross-team visibility for improved e-commerce growth.
Funneling employees toward collective growth with the assistance of machine-learning technology allows the collection of real-time insights on sales data, checkout simplicity and conversion rate to make predictive models used in directing company goals.
And for retailers, front-end management solutions that allow integration of widely used e-commerce platforms such as Shopify, Google Analytics and Facebook Ads, are smarter adoptions.
For Jonathan Smalley, chief executive officer of Yaguara, the opportunity to use ML-driven insights and KPI tools began in practice, wishing to better his own team in managing and reaching company goals.
With the ability to “recommend company-wide objectives, assign tasks, present real-time performance, share predictive insights,” among other objectives, the idea is to simplify the process of goal-setting and increase accountability for teams.
Deployment of ML-technology is seen as a long-term strategy for c-level executives seeking a competitive edge and reduced frustration in internal framework, and with better team management — business goals are not just collectively visible, but better achievable.