O documento discute como as empresas podem acelerar suas estratégias digitais usando inteligência artificial em áreas como curadoria de conteúdo, compra de mídia, criação de conteúdo, busca por voz e imagem, lead scoring, chatbots, personalização de conteúdo e serviço ao cliente preditivo. A inteligência artificial pode melhorar esses processos e fornecer experiências mais personalizadas para os clientes.
6. curadoria de conteúdo inteligente
de dados criados por
dia em 2025
bilhões GB
https://www.slideshare.net/Micro-Focus/growth-of-internet-data-2017
7. maior conversão que
posts não-UGC.
https://www.socialmediatoday.com/social-networks/how-user-generated-content-can-boost-performance-your-facebook-ads
Posts contendo
UGC tem X
curadoria de conteúdo inteligente
9. Descoberta de conteúdo e
curadoria para ajudá-lo a criar
uma biblioteca rica e facilmente
pesquisável de UGC para criar
experiências mais
personalizadas para o cliente.
curadoria de conteúdo
inteligente
12. das milhares de bids
feitas por empresas
estão erradas
https://pages.dataiku.com/hubfs/AI-Marketing-Usecase-Infographic.pdf
%McKinsey
estima que
compra de mídia
13. ROI com a
implementação de AI
powered ad tech.
https://adexchanger.com/agencies/ai-agency-lingerie-brand-cosabella-replaced-agency-artificial-intelligence/
%A marca de
lingerie Cosabella
aumentou
compra de mídia
15. Use a inteligência artificial
para veicular mensagens mais
relevantes e direcionadas nos
lugares certos, nos momentos
certos, fornecendo informações
baseadas em dados.
compra
de mídia
17. criação de conteúdo com IA
erro ortográfico/gramática
ruim é o fator que mais
prejudica a opinião sobre
uma marca nas mídias sociais
http://disruptive-communications.com/what-customers-hate-about-your-social-media-channels/
%
18. erros de escrita para cada
100 palavras, enquanto a
Coca comete 0.9.
https://www.ragan.com/infographic-battle-of-the-brands-grammar-edition/
Pepsi
comete
criação de conteúdo com IA
19. Inteligência artificial pode tornar
a prosa mais ousada, clara e
concisa, destacando frases
complexas e sugerindo diferentes
opções de palavras
criação de conteúdo
com IA
21. de fotos são carregadas
todos os dias.
milhões
https://www.forbes.com/sites/bernardmarr/2018/05/21/how-much-data-do-we-create-every-day-the-mind-blowing-stats-everyone-should-read
busca por voz & imagem
22. busca por voz & imagem
Compras baseadas
em voz devem
exceder
https://www.prnewswire.com/news-releases/voice-shopping-set-to-jump-to-40-billion-by-2022-rising-from-2-billion-today-300605596.html
bilhões
em 2022.
23. busca por voz & imagem
Até 2020,
Fonte: Gartner
%
de todas as buscas
serão realizadas através
de voz.
24. busca por voz & imagem
Anglian Home
Improvements
aumentou
https://www.epiphanysearch.co.uk/thoughts/preparing-for-voice-search-a-case-study
X
o tráfego das páginas
optimizando para busca
por voz.
25. busca por
voz & imagem
Conversational AI is what’s really
disrupting and shifting the
consumer behavior, and voice
search is just a component of that
bigger picture.
27. lead scoring baseado em IA
acredita que lead scoring é a
tática mais efetiva para
melhorar a receita.
https://www.cien.ai/lead-scoring/
%
28. lead scoring baseado em IA
acredita que “sinais errados”
são os principais desafios do
lead scoring.
https://www.salesforce.com/uk/blog/2018/08/predictive-lead-scoring-ai-sales-marketing.html
%
29. lead scoring baseado em IA
em apenas 30 dias e reduziu
custos operacionais em 35%
https://blog.peak.ai/just-a-heads-up-ai-does-lead-scoring-better-than-your-sales-team
%Regis aumentou
as vendas em
30. lead scoring baseado em IA
em 4 meses
https://www.saleswingsapp.com/lead-scoring/inbound-lead-qualification-case-study-saas-reviewcom/
K US$Princeton Review
obteve uma receita
adicional de
31. Um algoritmo de aprendizado de
máquina percorre um banco de
dados de dados do cliente e
estabelece tendências, padrões
reconhecidos e constrói um modelo a
partir dos dados, a fim de criar um
modelo de previsão.
lead scoring
baseado em IA
33. chatbots
Software de live
chat tem uma taxa
de satisfação de
https://learn.g2.com/facebook-chatbots
%
como a principal forma
de clientes engajarem
com uma marca
40. personalização
de conteúdos
Utilize IA para analisar o comportamento
do usuário, preferências, feedback e
características para prever o
comportamento e fornecer experiências
únicas e personalizadas.
42. serviço ao cliente preditivo
em churn de
clientes
https://www.forbes.com/sites/blakemorgan/2018/12/20/10-examples-of-predictive-customer-experience-outcomes-powered-by-ai/
Sprint
reduziu %
44. A análise preditiva explora os
padrões encontrados nos dados
históricos e transacionais para
prever o comportamento
futuro
serviço ao cliente
preditivo
46. ferramentas de recomendações
%De acordo com
McKinsey &
Company* do que os usuários assistem
no Netflix é referente a
recomendações.
https://www.mckinsey.com/industries/retail/our-insights/how-retailers-can-keep-up-with-consumers
47. %De acordo com
McKinsey &
Company*
da receita da Amazon.com
é gerada através de
mecanismos de
recomendações.
https://www.mckinsey.com/industries/retail/our-insights/how-retailers-can-keep-up-with-consumers
ferramentas de recomendações
48. O aprendizado de máquina ajuda os
profissionais de marketing a descobrir
quais tipos de produtos os
consumidores desejam com base em
seus comportamentos.
ferramentas de
recomendações
Research by SalesForce says 51 percent of consumers expect that by 2020 companies will anticipate their needs and make relevant suggestions before making contact6
Toyota has embraced UGC, using it to power Facebook ads for their annual "Feeling the Street" campaign.
Over six weeks, the campaign displayed the best UGC fans were sharing on Instagram, and received over 1.2 million collective likes, comments and shares. Without raising their budget from previous years, they achieved a 440% increase year over year ad engagement.
Toyota launched Feeling The Street – a global campaign aimed at highlighting and celebrating the world’s best street performers.
McKinsey estimates up to 30% of the thousands of pricing decisions companies make every year fail to deliver the best price
https://pages.dataiku.com/hubfs/AI-Marketing-Usecase-Infographic.pdf
identifying targets and keywords, moving budgets between channels, identifying fraud, controlling bids and executing buys.
In Q4, revenues increased 155% and the brand saw 1,500 more transactions year over year, 30% of which came from new customers.
Cosabella decreased costs by 12% by increasing returns by 50%.
Naturally, Jacobi kept using Albert. His dealership went from getting one qualified lead per day to 40. In the first month, 15% of those new leads were “lookalikes,” meaning that the people calling the dealership to set up a visit resembled previous high-value customers and therefore were more likely to make a purchase. By the third month, the dealership’s leads had increased 2930%, 50% of them lookalikes, leaving Jacobi scrambling to set up a new call center with six new employees to handle all the new business.
Products like Albert, MediaMath Omnichannel, Adgo, IBM Bid Optimizer and PredictiveBid are providing options which use the latest advancement in machine learning to optimize impressions in the real-time bidding process.
"Poor spelling or grammar" came in at 42.5 percent, far ahead of second-place "Updates are too 'sales-y'" at 24.9 percent.
Coca-Cola vs. Pepsi
Coca-Cola wins! Pepsi makes 3.6 writing mistakes per 100 words, but Coke only makes 0.9.
Facebook vs. Google
Google claims the prize here. Google only makes 1.1 writing mistakes per 100 words, but Facebook makes 4.3.
Ford vs. GM
This is a close race, but Ford comes out on top. GM makes a measly 1.3 mistakes per 100 words, but Ford only makes 0.5.
Grammarly vs Jetpack vs Ginger vs Hemingway vs Standard Spellchecker for WordPress
"Poor spelling or grammar" came in at 42.5 percent, far ahead of second-place "Updates are too 'sales-y'" at 24.9 percent.
"Poor spelling or grammar" came in at 42.5 percent, far ahead of second-place "Updates are too 'sales-y'" at 24.9 percent.
Anglian had three product FAQ areas for Conservatories, Doors, and Windows. All Q&A pages sat on a single page at a single URL; Anglian was answering multiple questions on a single page, which isn’t a great user experience, as not all of the questions were that closely related.
If Google’s job is to serve up the best answer for the query, why would it rank and serve up a ‘catch all’ page that doesn’t answer any question particularly in-depth?
Our solution was a dedicated product FAQ area, or ‘clinics’. The single page clinics were expanded into product specific clinic areas consisting of 39 or more pages.
Each of these clinics now consists of a hub which then links out to a dedicated page per each question and answer, and each answer was expanded - going from under 50 word answers to around 300 or more word answers.
1. Traditional or "rules-based" lead scoring: the scoring and ranking is set manually based on set of rules on a "IF this, THEN that" basis. For example, IF job title = "Account executive", THEN score lead highly.
2. Predictive or "algorithmic" lead scoring: instead of scoring a lead on a manually defined set of rules, a mathematical model examines the attributes of a "good" lead and infers the quality of all other leads to predict and rank their likely hood to close.
An AI enabled CRM platform has a particularly wide reach when it comes to collecting data: it automatically analyses customer data stored within your CRM, activity-based data (email, calendar, etc.), social data streams, and even any potential IoT data.
We pulled together data from Regit’s website and marketing systems, as well as from third-party datasets, such as from the DVLA, and applied some categorical machine learning models (as you do) to give predictions about the likelihood of users changing car. Lead scores were then pushed into Regit’s CRM system. Regit saw a 27% increase in sales and reduced operational costs by up to 35% by simply staffing the call-centre at the times of day most likely to result in a sale to a user or customer. I think we can all agree, they are some tasty figures.
Inbound lead qualification is key for any company generating leads through their website. Due to its popularity The Princeton Review was receiving an ever growing number of leads. Their inside sales team of 30 was looking at how to qualify these inbound effectively lacking a way to increase speed-to-lead to the low hanging fruits. InsideSales.com found in a study on sales acceleration that company’s who contact leads first increase their chance to take the deal home by up to 50% – which is especially true for more transactional sales cycles.
Toyota launched Feeling The Street – a global campaign aimed at highlighting and celebrating the world’s best street performers.
"Poor spelling or grammar" came in at 42.5 percent, far ahead of second-place "Updates are too 'sales-y'" at 24.9 percent.
"Poor spelling or grammar" came in at 42.5 percent, far ahead of second-place "Updates are too 'sales-y'" at 24.9 percent.
25 percent more bookings
$1 million in customer service email costs saved annually
50 percent year-over-year growth in users’ engagement with Julie
30 percent more revenue (monthly average) generated per booking
"Poor spelling or grammar" came in at 42.5 percent, far ahead of second-place "Updates are too 'sales-y'" at 24.9 percent.
"Poor spelling or grammar" came in at 42.5 percent, far ahead of second-place "Updates are too 'sales-y'" at 24.9 percent.
10% reduction in customer churn
40% increase in transactional NPS
40% increase in customers adding a line
8x increase in customer upgrades
Improvement in agent satisfaction
10% reduction in customer churn
40% increase in transactional NPS
40% increase in customers adding a line
8x increase in customer upgrades
Improvement in agent satisfaction