Análises preditivas avançadas em SEM
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Quer saber como prever se uma campanha irá funcionar ou não para seu negócio? Este webinar ensina como conectar o Ad Tech ao Marketing Tech, ajudando a tomar decisões estratégicas para sua compra de mídia, em tempo real! Aprenda a conectar sua estratégia de mídia aos seus KPIs de negócio e como reportar e reagir às tendências que podem afetar o seu negócio. Palestrante: Fernando Takahashi - Estrategista de marketing digital na Adobe responsável por toda a área de Data Driven Marketing e Acquisition Acceleration. Bio: É formado em Marketing pela Anhembi Morumbi e tem mais de 18 anos de experiência em tecnologias voltadas para o marketing online e offline. Já passou por empresas como Y&R, Grey, Ogilvy, DraftFCB, além de anunciantes como o Pão de Açucar.
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Análises preditivas avançadas em SEM
- 2. © 2016 Adobe Systems Incorporated. All Rights Reserved. Adobe Confidential. IAB – Análises Preditivas e Avançadas em SEM Fernando Takahashi | Principal Digital Marketing Strategist
- 3. © 2016 Adobe Systems Incorporated. All Rights Reserved. Adobe Confidential.© 2016 Adobe Systems Incorporated. All Rights Reserved. Adobe Confidential. Maximizar a performance 3 Esforço Ciclista #1 – 100% Ciclista #2 – Ciclista #3 – 71% 64%
- 4. © 2016 Adobe Systems Incorporated. All Rights Reserved. Adobe Confidential.© 2016 Adobe Systems Incorporated. All Rights Reserved. Adobe Confidential. Ad Tech + Mar Tech = Visão clara dos KPIs de negócio Tráfeg o Conversão KPIs Calculados Conversõe s Offline Margem Devoluçõe s Custo de Venda
- 5. 5 Três relatórios escondidos em cada keyword
- 6. © 2016 Adobe Systems Incorporated. All Rights Reserved. Adobe Confidential.© 2016 Adobe Systems Incorporated. All Rights Reserved. Adobe Confidential. Segmentação das Keywords Convertem? Sim Os Clicks estão acima do limite de eficiência? Não (Continue Monitorando) Sim Está dentro do ROI? Sim Acima do limite de posição? Sim Cash Cows Não Stars Não Acima do limite de volume de impressão? Sim Loss Leaders Não Erratic Não Os Clicks estão acima do limite de conversão? Sim Influenciadores de conversão? Sim Feeders Não Dead & Done Não (Continue Monitorando)
- 7. © 2016 Adobe Systems Incorporated. All Rights Reserved. Adobe Confidential.© 2016 Adobe Systems Incorporated. All Rights Reserved. Adobe Confidential. Resultados Custo Impressões Conversões Sem Conversões Baixo tráfego Segmentos Outliers Custo Extremanente Alto = Diminuir, Pausar CPC Alto e Quality Score Baixo = Diminuir, Relevância & revisar Match Type CTR Baixo e Grande Qt. de Impressões= Negativações & Alinhamento Anúncio Alta qt. Impressões e Posições baixas = Aumentar Alta qt. de Impressões e Boas Posições = Diminuir, Rever Relevância de Anúncios Quality Score baixo e Baixo Volume = Aumentar, Rever Targeting & Relevância ROAS Ruim & Posição Premium = Diminuir ROAS Bom & Volume Significativo = Aumentar Segmentação das Keywords
- 8. © 2016 Adobe Systems Incorporated. All Rights Reserved. Adobe Confidential.© 2016 Adobe Systems Incorporated. All Rights Reserved. Adobe Confidential. Líderes em Volume 8
- 9. © 2016 Adobe Systems Incorporated. All Rights Reserved. Adobe Confidential.© 2016 Adobe Systems Incorporated. All Rights Reserved. Adobe Confidential. Ameaças à Eficiência 9
- 10. © 2016 Adobe Systems Incorporated. All Rights Reserved. Adobe Confidential.© 2016 Adobe Systems Incorporated. All Rights Reserved. Adobe Confidential. Posições Negligenciadas 10
- 11. 11 Entenda o valor Holístico das micro-conversões
- 12. © 2016 Adobe Systems Incorporated. All Rights Reserved. Adobe Confidential. 12 Não olhar para a Foto Inteira pode ser perigoso! © 2016 Adobe Systems Incorporated. All Rights Reserved. Adobe Confidential. 12
- 13. Integração Ad Tech e Mar Tech: Analytics Others N/ADiferença Integrado Dados de Analytics Comportamento no site e engajamento Não- Integrado
- 14. Colete dados de forma integrada através de todo o funil OthersEverybod y Else Others Disponivel através de integrações com ferramentas de analytics Buscas/Keywords Impressões Clicks Conversão Comportamento pós-click • Compra • Engajamento: tempo gasto/re-visitas • Visualizações de página/produto • Bounce Rate (Taxa de rejeição) • Outras métricas de engajamento ”Feeds” das Search Engines Tracking de conversão Não disponíveis sem uma integração
- 15. 15 Saiba como seus indicadores de performance trabalham juntos Resultado por impressão CTR Taxa de rejeição (Bounce Rate) Taxa de Conversão Impressões Clicks Engajamento Conversão
- 16. 16 Este tipo de integração também permitirá que os analistas aprofundem as análises, correlacionando outras dimensões com os resultados de campanha. Este tipo de análise permitirá um conhecimento muito melhor do funcionamento das keywords, campanhas e até auxiliar na distribuição de verba de acordo com os resultados obtidos. Número da Visita Fidelidade do cliente (Novo, Retornante, Consumidor leal) Línguas Fuso horário Geo-Segmentação (País, Estado/ Província / Região, Cidade, CEP, DMA) Navegador Sistema Operacional Resolução do Monitor Tipo de Conexão Operadora CelularHorário do dia Dia da Semana Acima estão somente alguns exemplos. De acordo com seu objetivo de negócio, outras métricas podem ser definidas. Saiba como seus indicadores de performance trabalham juntos
- 17. © 2016 Adobe Systems Incorporated. All Rights Reserved. Adobe Confidential. Final Conversions Micro- Conversions Engagement Metrics Identificar Influenciadores Leads iniciados vs Vendas Custo Impressões Convertidos Sem Conversões Ignorados Tempo no site Bounce Rate Métricas de Engajamento
- 18. 18 Adobe.com Insights • Search Engine e Site
- 19. 19 Adobe.com Insights • Search Engine e Site • Estrutura de Campanha • KW por Anúncio
- 20. 20 • Search Engine e Site • Estrutura de Campanha • KW Pesquisada • Keyword por Search Query • Keyword por Busca Interna Adobe.com Insights
- 21. 21 • Search Engine e Site • Estrutura de Campanha • KW Pesquisada • Insights Modificadores de Bid• Campanha por hora • Campanha por demográficos • Contas por Geo Adobe.com Insights
- 22. 22 • Search Engine e Site • Estrutura de Campanha • KW Pesquisada • Insights Modificadores de Bid • Produtos • Campanha por Produto Adobe.com Insights
- 23. 23 • Search Engine e Site • Estrutura de Campanha • KW Pesquisada • Insights Modificadores de Bid • Produtos • Retenção do visitante• Keyword por Tempo Gasto • Keyword por No. da Visita Adobe.com Insights
- 24. © 2016 Adobe Systems Incorporated. All Rights Reserved. Adobe Confidential. 24 Use a automação para alavancar ao invés de substituir
- 25. © 2016 Adobe Systems Incorporated. All Rights Reserved. Adobe Confidential. 25 Precisão é muito importante em otimizações Los Angeles Philadelphia New York City Performance Maximization
- 27. 27 INSIGHTS
- 28. • Desequilibrado • Somente Manual = Perda de oportunidades. Estresse. • Somente Automação = Otimização exagerada. • Equilibrado • Manual para as anomalias = Responsivo sem estressar • Regras para as prioridades baixas = Foco para campanhas de maior importância • Portfolios = Automação do media mix. Duas cabeças pensam melhor do que uma. Tempo $$$$Tempo $$$$Tempo $$$$ Manual Volume Auto Eficiência
- 29. Tracking Dados das Search Engines Dados de comportamento no site vindo de Analytics Conversões Clicks Impressão Engajamento no site • Visualizações pg/prod • Tempo Gasto • Taxa de rejeição • Micro-conversões Clicks Ad Set/KW+MT Comportamento no site Conversões 4 4 • Média 5 Visualizações por visita • 10% Bounce • Múltiplas visitas • Tempo médio gasto no site: 4:10 • Média de 1.5 visualizações por visita • 75% Bounce • Sem visitas adicionais • Tempo médio gasto no site: 0:20 0 01 Não disponíveis Keyword 1 Keyword 2 +28% Bid -31% Bid Automação das modificações de Bid Automação ajuda a alavancar oportunidades Q: Como vocês comprariam estas duas kw?
- 30. Mesmo ”Bid” ($ 0.72), Performance diferente Posição MédiaCPC MédioCTRClicksCustoBid O aumento de performance pode ser alcançado se ”bidarmos” cada keyword baseado em seu valor para o negócio. * measured from Sep 1, 2015-Sep 30, 2015 Google Main acct, active keywords only
- 31. Modelos Preditivos por Bid Unit | Transparência total dos dados
- 32. Objetivos Ponderados Campanha de Branding Impressões / Clicks Profundidade da navegação: 20% Tempo gasto no site: 30% Assistiu a um vídeo ou baixou um material ou se inscreveu em um formulário: 50%
- 34. Recomendações de Mix de Mídia (Portfolio)
- 35. Otimização em todos os níveis Portfolio Engine Account Campaign Ad Group Keyword Bid Unit
- 36. Automação de Bids 36 First PPC Platforms Enhanced Campaigns AdWords Real-Time Bidding Shopping Campaigns Complexity
- 37. DIMENSIONAL PORTFOLIOREGRAS Níveis de maturidade na automação de bids KW1 KW2 Desktop Mobile SaturdayFridayThursdayWednesdayTuesdayMondaySunday SaturdayFridayThursdayWednesdayTuesdayMondaySunday Desktop Mobile SaturdayFridayThursdayWednesdayTuesdayMondaySunday SaturdayFridayThursdayWednesdayTuesdayMondaySunday KW1 KW2 KW1 KW2 PORTFOLIO
- 38. DIMENSIONAL PORTFOLIOREGRAS PORTFOLIOObjetivo: Gerar o maior número possível de conversões a ≤ $20 CPA $20 CPA 25 Conversions KW1 DESKTOP KW2 MOBILE KW2 DESKTOP KW1 MOBILE $20 CPA 30 Conversions $20.61 CPA 33 Conversions $15.33 CPA 21 Conversions KW1 KW2 Níveis de maturidade na automação de bids
- 39. Atribuição 39 Canal 4 Canal 3 Canal 2 Canal 1
- 40. “Multi-touch Insights” e Otimização 40 Last Event First Event Even Weight First More Weight Last More
- 41. 41 TEMPO
- 42. 42 Estimativas de economia de tempo Search Tempo gasto antes (horas) % de economia de tempo Tempo gasto depois (horas) Otimização Manual de Bids 15.00 80% 3.00 Criação de novas campanhas (estrutura, palavras-chave, negativações) 10.00 30% 7.00 Composição de relatórios 5.00 70% 1.50 Otimização de Landing Page (Testes A/B) 3.75 30% 2.63 Testes de Criativo (headlines, ETA, etc) 3.00 35% 1.95 Expansão de palavras-chave 2.00 25% 1.50 Monitoramento de Search Queries, Expansões 2.00 25% 1.50 Descoberta de novas palavras-chave 1.25 25% .94 Total 42.00 52% 20.01
- 43. Foco de tempo das análises Tarefas Horas gastas Criação de Campanha 25.00 Bid Manual 20.00 Relatórios 11.00 Planejamento 5.00 Expansão 5.25 Testes/Otimização 16.75 Tarefa Horas gastas Criação de Campanha 25.00 Bid Manual 20.00 Relatórios 11.00 Planejamento 5.00 Expansão 5.25 Testes/Otimização 16.75 Baixo Valor Alto Valor 67% 33% Task Hours Spent Criação de Campanhas 25.00 Manual Bidding 20.00 Relatórios 11.00 Planning 5.00 Expansão 5.25 Testing/Optimization 16.75 Tarefa Horas gastas Criação de Campanha 25.00 Bid Manual 20.00 Relatórios 11.00 Planejamento 5.00 Expansão 5.25 Testes/Otimização 16.75 Baixo Valor Alto Valor 22% 78% Sem ferramentas Com ferramentas
- 44. 44 CRESCIMEN TO
- 45. Adobe.com | Melhorias na previsão de resultados 0.00% 20.00% 40.00% 60.00% 80.00% 100.00% 120.00% 140.00% 160.00% 180.00% 1 2 3 4 5 6 7 8 9 10 11 12 Accuracy (100%isthebest) Portfolio old model new model 92.03% Accurate82.26% Accurate
- 46. Adobe.com | Melhorias no RPC e no ROI 0 1 2 3 4 5 6 7 8 rpc roi Portfolio APre Post rpc roi Portfolio B +66.6% +70.4% +19.5% +5.7%
- 47. Os Insights do gestor de negócio são expandidos Começo Meio Fim Solução e Próximos Passos Compartilhe as recomendações e discuta os próximos passos Elevando os Insights Compartilhe descobertas que revelam análises mais profundas do problema ou oportunidade Momento ”A-ha” Apresente a maior descoberta ou Insight- chave Set-up Contexto da situação atual, personagem(n s) e o gancho Gustav Freytag (1816-1895) Entregando suas análises
- 48. Construindo sua história com dados Momento ”A-ha” Pense neste momento primeiro. Ele é o "clímax" da sua história. Tudo deve convergir para ele. Set-up Procure destacar o impacto do contexto nos negócios Elevando os Insights Compartilhe descobertas que ajudem a construir o momento A-ha Solução e próximos passos Determine estratégias de ação curtas e que demonstrem resultados mais rapidamente, para gerar tração, sempre visando o objetivo final.
- 49. Como esta estrutura se compara a outros modelos? Passado Presente Futuro Set-Up Elevando os Insights Momento ”A-ha” Solução e Próximos Passos Problema Solução Benefício O que? E daí? E agora?
Editor's Notes
- Does anyone kNãow why Ciclistas ride like this? (Drafting) When riding in a pace line, how much effort do you think the second Ciclista is giving? Third Ciclista? Performance is Nãot only about playing your best, but playing the smartest. 29% energy savings over a 100-mile course adds up to a huge boost in performance.
- Lead Started/Initiated Lead Completed Final Sale from Lead Scottrade – customer score = credit score, trade volume, trade values, etc.
- Overcome bid inertia by separating the three hidden parts of every keyword report Zoom in to each colored block and show some example data
- WHAT TO LOOK FOR The above screenshot of the performance Segmentos goes into more detail, but here is the general idea: Reward the most efficient converting keywords with higher bids to trade some of that efficiency for more volume at a higher position Punish the most inefficient converting keywords with lower bids to re-establish balance between volume and efficiency for the maximum profit If micro-conversions were included, decrease keywords with the highest spend more slowly than you would with obviously wasteful keywords. (Investigate the conversion path to see if the site could be adjusted to lead more visitors to the final conversion) Pull back aggressively on Sem Conversões keywords with the most spend. Even the best accounts have 5-10 keywords at the top of this segment that are responsible for the majority of waste. (This is where solutions like the Cross Visit Participation VISTA rule can help you validate whether these keywords are valuable "root" terms that are resulting in a large number of assists or conversions from a different allocation perspective or attribution model. However, until you can prove that theory with data avoid ego bidding and make sacrifices according to the data available to you). Pause or significantly reduce the bids of keywords with an extremely high number of Impressões that have not led to any clicks. "Extremely high" will vary for the unique situation and environment of each account, but a 1% CTR is generally accepted as a lenient benchmark for any industry. If a keyword has thousands of Impressões in a top fold position without any clicks, its quality score should be improved with better ad alignment before bidding will make much of a difference. However, if a keyword has received a significant number of Impressões with no clicks at a low position, consider increasing the bid to give the keyword's ad a better chance of getting noticed so that more valuable metrics can be used to measure the keyword's conversion potential. Clearly explain that the stars represent outliers Each keyword segment should be optimized towards the most appropriate KPI Then you can simply focus on the 80/20 concept and handle the top and bottom Then let automation handle anything that is not an extreme The obvious Segmentos are converting, non-coverting Custo, and clickless searches Smooth out the Segmentos by falling back to multiple microconversios and time frames Allocation: Orders (Last Click) Orders (First Click) Assists (Orders in the Middle) Retail: Orders Cart Adds Product Views Long Term Orders Because these are complex business decision that must be adapted to each unique situation, these are the types of things that should not be delegated to a machine. ASSUMPTIONS "Sem Conversões" has become increasingly difficult to define as many have begun preaching that "last click is dead". Although I agree that difficult questions must be asked to determine whether default attribution models should be accepted, real world experience has shown that a small number of keywords actually point marketers towards a different type of optimization when viewed from some other perspective like first, last, linear, weighted, etc. The few keywords that do prove their worth outside of the last click model are definitely worth digging for. SearchCenter and SiteCatalyst can use the CVP (Cross Visit Participation) VISTA rule to provide users with very flexible attribution models. Once it is implemented, users simply add similar conversion metrics in different allocation perspectives with a single click just like they would for any other metric. Since the development of the CVP VISTA rule over a year ago, "Assists" have grown to become one of the most powerful micro-conversions available. However, the majority of clients who still do not have the CVP VISTA rule implemented should let fear and paranoia prevent them from taking action on the valuable data already available to them. It is better to learn from action and mistakes than to wait passively and make excuses with unproven theories. TIM WADDEL FEEDBACK ON ROUGH DRAFT Keyword Segmentation similar to Audience Segmentation in Display Those that read reviews, added something to the cart Responding with retargeting based on that last action Attribution / Assists Through attribution, how can you more easily identify the varied roles of keywords based on their different position in the funnel Balanced with avoiding paranoia. Dont let the assists prevent you from the obvious. Build awareness in the ES solution (who cares about "productized") In the meantime, use what you have. You dont have to boil the ocean. Guilty until proven innocent. Avoid ego bidding. The segmetation slides made sense to me last year, how can we make that even more clear with real examples and visualization instead of words
- The difference – what no one else can offer – is a complete picture of your conversion pipeline - Having a fuller picture means you can more clearly see value and effectively chase qualified visitors, putting more in the top of your pipeline, and getting more out of it on the bottom line
- What data is available to us and how can we collect them along the ad conversion funnel
- For the offline data solution in analytics to work we need to configure the report suite for this option, and you need to load a feed into analytics which has the “hidden” transaction ID + the offline conversion metrics you want to associate, + the transaction date for those metrics. If your s_code has set the following: S.transactionid=s.purchaseid Then the transition ID you use will be the purchase ID – this simplifies things quite a bit. If you have Nãot done the above, then you’ll have to find the transaction ID for each conversion and I don’t kNãow exactly where you get that information. I think you can report out on that Nãow – but Nãot sure which report.
- Clearly explain that the stars represent outliers Each keyword segment should be optimized towards the most appropriate KPI Then you can simply focus on the 80/20 concept and handle the top and bottom Then let automation handle anything that is not an extreme The obvious Segmentos are converting, non-coverting Custo, and clickless searches Smooth out the Segmentos by falling back to multiple microconversios and time frames Allocation: Orders (Last Click) Orders (First Click) Assists (Orders in the Middle) Retail: Orders Cart Adds Product Views Long Term Orders Because these are complex business decision that must be adapted to each unique situation, these are the types of things that should not be delegated to a machine.
- Let’s say you’re flying from LA to NYC. Unfortunately you board a Southwest flight (Missouri wrong airport reference) whose compass is off by one degree. Where do you think you would land? Accuracy is paramount in flight as well as in our models. If we project a return rate at a certain bid amount, we need to do it accurately.
- With more than 110 product development resources, we are constantly inNãovating and releasing new updates to the product. We have releases every 2 weeks, which enables us to consistently beat our competition to market with new search engine API features. We were first to market with support of Google Enhanced Campaigns, first to market with support for Google Product Listing Ads (PLAs) and first to market with support for Yandex and the latest version of Yahoo Japan. And because we’re profitable, unlike all of our competitors, we are continuing to grow our development resources to get even faster.
- With more than 110 product development resources, we are constantly inNãovating and releasing new updates to the product. We have releases every 2 weeks, which enables us to consistently beat our competition to market with new search engine API features. We were first to market with support of Google Enhanced Campaigns, first to market with support for Google Product Listing Ads (PLAs) and first to market with support for Yandex and the latest version of Yahoo Japan. And because we’re profitable, unlike all of our competitors, we are continuing to grow our development resources to get even faster.
- Just Human / Manual = Stress and missed opportunities Only Automation / Rules = Failure and over-optimization
- With more than 110 product development resources, we are constantly inNãovating and releasing new updates to the product. We have releases every 2 weeks, which enables us to consistently beat our competition to market with new search engine API features. We were first to market with support of Google Enhanced Campaigns, first to market with support for Google Product Listing Ads (PLAs) and first to market with support for Yandex and the latest version of Yahoo Japan. And because we’re profitable, unlike all of our competitors, we are continuing to grow our development resources to get even faster.
- With more than 110 product development resources, we are constantly inNãovating and releasing new updates to the product. We have releases every 2 weeks, which enables us to consistently beat our competition to market with new search engine API features. We were first to market with support of Google Enhanced Campaigns, first to market with support for Google Product Listing Ads (PLAs) and first to market with support for Yandex and the latest version of Yahoo Japan. And because we’re profitable, unlike all of our competitors, we are continuing to grow our development resources to get even faster.
- Better forecasting meant better bidding, which delivered tangible results on the bottom line – improved RPC and ROI.
- Let’s look at the same structure from a data perspective. First, you start with the set-up where you provide background on the current situation, characters, and the hook. The hook is the inciting incident where you reveal there’s a problem or opportunity. You then share additional findings that provide deeper insights into the problem or opportunity. Eventually, you reach the climax of your presentation where you share your main finding or insight, which should be monetized so that it catches the attention of your audience. How quickly you get to your aha moment will depend on your analysis – some may not have as many layers and won’t need as much build-up. Then we jump to the recommended solution and potential next steps. Through this process your audience’s knowledge is expanded. Now let’s dig into how you can leverage this data storytelling arc.