Presentación Kelly Cronin - eCommerce Day Lima 2016
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Diapositivas presentadas por Kelly Cronin, Gerente de Canales Virtuales & eCommerce Grupo Efe, en el eCommerce Day Lima 2016
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Presentación Kelly Cronin - eCommerce Day Lima 2016
- 1. Grupo EFE Electrodomésticos, Motos y Financiemiento Kelly Cronin Gerente de eCommerce Grupo EFE @kellycroninj https://www.linkedin.com/in/croninkelly OMNICHANNEL EN LA PRÁCTICA. ¿CÓMO INTEGRAR EL CANAL ONLINE CON EL OFFLINE? SUCCESS STORIES
- 3. Capturar emails en el punto de venta Envíos con mensaje de valor dentro de la tienda Asunto: Welcome to the Team
- 5. Pick up & Return Lockers Puede ser usados para compras online y Offline
- 8. Mobile Ordering for in-store pickup
- 9. Omnichannel customers spend 3-4x times more than single-channel customers do.
- 10. Donde Iniciar? Indexar tus locales físicos en Google por “Google Mi Negocio”
- 11. Generar Base de datos tanto offline y online. Segmentar tu base de datos online para hacer acciones offline. Cliente interactúa primera vez • Contáctanos • Más información • Compra Cliente entra serie de recibir mailings masivos por un periodo de tiempo corto Termina el periodo corto, y se quita el cliente del segmento masivo, y lo marca solo para los segmentos con cuales se ha interactuado • Cliente recibe 15 emails distintos en 30 días • Cliente solo hizo clic en emailing de “Ahora puedes pagar en cuotas” Entra segmento “financiamiento”
- 12. Maximizar esfuerzos del call center para cerrar ventas offline que inician online por Lead Scoring Lead Scoring – clasificación objetiva de un lead de venta frente a otro 1. Concentrarse en: Gente, Procesos y Tecnologia 2. Definir puntuaciones de los leads Interacciones Email (Clicks / Opens) Formulario (Fills Out Form) Web Descargas Visitas de Paginas Clicks Cambio de Status de un Programa Registración de eventos Asistencia de eventos Score Decay Falta de interacción o actividad con la pagina Vistando ciertas paginas (Pagina de “Trabaja con nosotros”)
- 13. Lead Scoring – clasificación objetiva de un lead de venta frente a otro 3. Asigna acciones por puntuación Ej. Leads >100 puntos: Asunto: Lead de alta prioridad Estimados Sales Team: {systems.fullname} ya se encuentra como prioridad para contactar. Su Lead Score es {systems.leadscore}. Su información de contacto es: {systems.telephone} Ya las 3 ultimas interacciones han sido: {systems.interaction} {systems.interaction + 1} {systems.interaction + 2} Saludos, Marketing team
- 14. Consejos & Recomendaciones • MEDIR todo! – Capturar emails en tienda para medir como acciones online afecta offline. • Base de Datos Centralizados. • Involucrar toda la empresa, y tener claro tus necesidades para buscar soluciones buenos y baratos.
Notas del editor
- tation of a “buy-online, pickup-in-store” (BOPS) project. The implementation of this project is associated with a reduction in online sales and an increase in store sales and traffic. These results can be explained by two simultaneous phenomena: (1) additional store sales from customers who use the BOPS functionality and buy additional products in the stores (cross-selling effect) and (2) the shift of some customers from the online to the brick-and-mortar channel and the conversion of noncustomers into store customers (channel-shift effect). We explain these channel shift patterns as an increase in “research online, purchase offline” (ROPO) behavior enabled by BOPS implementation, and we validate this explanation with evidence from the change of cart abandonment and conversion rates of the brick-and-mortar and online channels. We interpret these results in light of recent operations management literature that analyzes the impact of sharing inventory availability information. Our analysis illustrates the limitations of drawing conclusions about complex interventions using single-channel data.
- tation of a “buy-online, pickup-in-store” (BOPS) project. The implementation of this project is associated with a reduction in online sales and an increase in store sales and traffic. These results can be explained by two simultaneous phenomena: (1) additional store sales from customers who use the BOPS functionality and buy additional products in the stores (cross-selling effect) and (2) the shift of some customers from the online to the brick-and-mortar channel and the conversion of noncustomers into store customers (channel-shift effect). We explain these channel shift patterns as an increase in “research online, purchase offline” (ROPO) behavior enabled by BOPS implementation, and we validate this explanation with evidence from the change of cart abandonment and conversion rates of the brick-and-mortar and online channels. We interpret these results in light of recent operations management literature that analyzes the impact of sharing inventory availability information. Our analysis illustrates the limitations of drawing conclusions about complex interventions using single-channel data.
- tation of a “buy-online, pickup-in-store” (BOPS) project. The implementation of this project is associated with a reduction in online sales and an increase in store sales and traffic. These results can be explained by two simultaneous phenomena: (1) additional store sales from customers who use the BOPS functionality and buy additional products in the stores (cross-selling effect) and (2) the shift of some customers from the online to the brick-and-mortar channel and the conversion of noncustomers into store customers (channel-shift effect). We explain these channel shift patterns as an increase in “research online, purchase offline” (ROPO) behavior enabled by BOPS implementation, and we validate this explanation with evidence from the change of cart abandonment and conversion rates of the brick-and-mortar and online channels. We interpret these results in light of recent operations management literature that analyzes the impact of sharing inventory availability information. Our analysis illustrates the limitations of drawing conclusions about complex interventions using single-channel data.
- tation of a “buy-online, pickup-in-store” (BOPS) project. The implementation of this project is associated with a reduction in online sales and an increase in store sales and traffic. These results can be explained by two simultaneous phenomena: (1) additional store sales from customers who use the BOPS functionality and buy additional products in the stores (cross-selling effect) and (2) the shift of some customers from the online to the brick-and-mortar channel and the conversion of noncustomers into store customers (channel-shift effect). We explain these channel shift patterns as an increase in “research online, purchase offline” (ROPO) behavior enabled by BOPS implementation, and we validate this explanation with evidence from the change of cart abandonment and conversion rates of the brick-and-mortar and online channels. We interpret these results in light of recent operations management literature that analyzes the impact of sharing inventory availability information. Our analysis illustrates the limitations of drawing conclusions about complex interventions using single-channel data.
- tation of a “buy-online, pickup-in-store” (BOPS) project. The implementation of this project is associated with a reduction in online sales and an increase in store sales and traffic. These results can be explained by two simultaneous phenomena: (1) additional store sales from customers who use the BOPS functionality and buy additional products in the stores (cross-selling effect) and (2) the shift of some customers from the online to the brick-and-mortar channel and the conversion of noncustomers into store customers (channel-shift effect). We explain these channel shift patterns as an increase in “research online, purchase offline” (ROPO) behavior enabled by BOPS implementation, and we validate this explanation with evidence from the change of cart abandonment and conversion rates of the brick-and-mortar and online channels. We interpret these results in light of recent operations management literature that analyzes the impact of sharing inventory availability information. Our analysis illustrates the limitations of drawing conclusions about complex interventions using single-channel data.
- NOT international
- tation of a “buy-online, pickup-in-store” (BOPS) project. The implementation of this project is associated with a reduction in online sales and an increase in store sales and traffic. These results can be explained by two simultaneous phenomena: (1) additional store sales from customers who use the BOPS functionality and buy additional products in the stores (cross-selling effect) and (2) the shift of some customers from the online to the brick-and-mortar channel and the conversion of noncustomers into store customers (channel-shift effect). We explain these channel shift patterns as an increase in “research online, purchase offline” (ROPO) behavior enabled by BOPS implementation, and we validate this explanation with evidence from the change of cart abandonment and conversion rates of the brick-and-mortar and online channels. We interpret these results in light of recent operations management literature that analyzes the impact of sharing inventory availability information. Our analysis illustrates the limitations of drawing conclusions about complex interventions using single-channel data.
- tation of a “buy-online, pickup-in-store” (BOPS) project. The implementation of this project is associated with a reduction in online sales and an increase in store sales and traffic. These results can be explained by two simultaneous phenomena: (1) additional store sales from customers who use the BOPS functionality and buy additional products in the stores (cross-selling effect) and (2) the shift of some customers from the online to the brick-and-mortar channel and the conversion of noncustomers into store customers (channel-shift effect). We explain these channel shift patterns as an increase in “research online, purchase offline” (ROPO) behavior enabled by BOPS implementation, and we validate this explanation with evidence from the change of cart abandonment and conversion rates of the brick-and-mortar and online channels. We interpret these results in light of recent operations management literature that analyzes the impact of sharing inventory availability information. Our analysis illustrates the limitations of drawing conclusions about complex interventions using single-channel data.
- tation of a “buy-online, pickup-in-store” (BOPS) project. The implementation of this project is associated with a reduction in online sales and an increase in store sales and traffic. These results can be explained by two simultaneous phenomena: (1) additional store sales from customers who use the BOPS functionality and buy additional products in the stores (cross-selling effect) and (2) the shift of some customers from the online to the brick-and-mortar channel and the conversion of noncustomers into store customers (channel-shift effect). We explain these channel shift patterns as an increase in “research online, purchase offline” (ROPO) behavior enabled by BOPS implementation, and we validate this explanation with evidence from the change of cart abandonment and conversion rates of the brick-and-mortar and online channels. We interpret these results in light of recent operations management literature that analyzes the impact of sharing inventory availability information. Our analysis illustrates the limitations of drawing conclusions about complex interventions using single-channel data.
- tation of a “buy-online, pickup-in-store” (BOPS) project. The implementation of this project is associated with a reduction in online sales and an increase in store sales and traffic. These results can be explained by two simultaneous phenomena: (1) additional store sales from customers who use the BOPS functionality and buy additional products in the stores (cross-selling effect) and (2) the shift of some customers from the online to the brick-and-mortar channel and the conversion of noncustomers into store customers (channel-shift effect). We explain these channel shift patterns as an increase in “research online, purchase offline” (ROPO) behavior enabled by BOPS implementation, and we validate this explanation with evidence from the change of cart abandonment and conversion rates of the brick-and-mortar and online channels. We interpret these results in light of recent operations management literature that analyzes the impact of sharing inventory availability information. Our analysis illustrates the limitations of drawing conclusions about complex interventions using single-channel data.
- Buy Online Pickup In Store (BOPS) Importante crear estrategias de: Research online Purchase Offline (ROPO) 75% de consumadores Savy Research Online antes de comprar. 72% de consumadores Savy Research Online y Compran Offline Ayuda siempre tus clientes que buscan de ti online que faciliten llegar a ti offline. Kioskos y Ventas online dentro de tienda fisica Lead scoring con triggers para optimizar acciones offline