experimento A/B: Hipótese e Métricas de Entrega Shopee
O propósito deste experimento é determinar se a exibição de uma estimativa de entrega mais precisa na página do produto afeta a taxa de conversão. Nossa hipótese central é: ‘Mostrar um intervalo de entrega mais estreito (por exemplo, 2-3 dias em vez de 2-5 dias) expandirá a taxa de conversão em pelo menos 5%’.
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Para medir o sucesso, definiremos duas métricas principais: a taxa de conversão (número de compras dividido pelo número de visitantes da página do produto) e o tempo médio gasto na página do produto. Um aumento na taxa de conversão, acompanhado de um tempo médio na página similar ou superior, indicará um desfecho positivo.
O grupo de controle observará a estimativa de entrega padrão fornecida pela Shopee. Por outro lado, o grupo experimental observará uma estimativa de entrega refinada, calculada com base em informações históricos de entrega para rotas específicas. Vale destacar que a duração do experimento será de duas semanas, tempo suficiente para coletar informações estatisticamente significativos, considerando o volume de tráfego.
Os recursos necessários incluem acesso aos informações de entrega da Shopee, ferramentas de experimento A/B (como Google Optimize) e desenvolvedores para executar as alterações na página do produto.
Navegando Pelos Mares da Entrega: Uma Jornada
Imagine a experiência de compra como uma jornada marítima. O cliente, o navegador, anseia por chegar ao seu destino, o produto desejado. A estimativa de entrega é o mapa, guiando-o através das incertezas do tempo e da distância. Uma estimativa vaga é como um mapa impreciso, cheio de névoa e promessas incertas. Isso pode levar à frustração e ao abandono da jornada.
No entanto, uma estimativa precisa é como um mapa detalhado, revelando os atalhos e os perigos potenciais, construindo confiança e incentivando o navegador a continuar sua jornada. É fundamental compreender que a precisão não é apenas sobre cumprir prazos, mas também sobre gerenciar expectativas.
Assim, o experimento A/B se torna a bússola que nos guia. Ele nos permite comparar diferentes mapas (estimativas de entrega) e determinar qual deles leva o navegador (cliente) ao destino com maior segurança e satisfação. O experimento demonstra que a clareza e a precisão são as estrelas que guiam o sucesso da experiência de compra.
Shopee: Testando e Melhorando o Tempo de Entrega
Então, como aplicamos isso na prática? Digamos que você venda camisetas na Shopee. Atualmente, a plataforma mostra uma estimativa de entrega de ‘3-7 dias úteis’. Que tal testarmos algo mais específico? Para um grupo de clientes, mostramos ‘3-4 dias úteis’ se os informações históricos apontarem para essa média.
Outro aspecto relevante é que, para executar este experimento, precisamos de acesso à ferramenta de A/B testing da Shopee (se disponível) ou integrar uma ferramenta externa. Também precisamos de um desenvolvedor para alterar a forma como a estimativa de entrega é exibida.
Por fim, ao final das duas semanas, analisaremos os resultados. Se a taxa de conversão do grupo que viu a estimativa mais precisa aumentou significativamente, teremos validado nossa hipótese! E, nesse caso, implementaremos essa mudança para todos os clientes. É um trajetória simples, mas que pode gerar grandes resultados!
