AI Marketing is a combination of AI principles and applications directly applied to Marketing concepts to target, acquire and retain customers.
In a short span of time, Artificial Intelligence and Machine Learning (AI ML) have become the central marketable assets for SaaS and Cloud businesses. “Technology Maturity” of the organizations which are already offering and leveraging AI ML and data infrastructure in the Cloud range from start-ups, to innovators and pioneers, to leaders and trend-setters.
The worldwide public cloud services market is projected to grow 17.5 percent in 2019 to total $214.3 billion, up from $182.4 billion in 2018, according to Gartner, Inc. Forrester predicts the Public Cloud market to reach $411 billion by 2022.
“Fewer, but larger, Public Cloud platform providers and a maturing SaaS ecosystem will dominate Enterprise Cloud spending. CIOs should use this forecast to benchmark the pace and shape of their public Cloud strategies.”
Sid Nag, Research Vice President at Gartner, said –
“Cloud services are definitely shaking up the industry. At Gartner, we know of no vendor or service provider today whose business model offerings and revenue growth are not influenced by the increasing adoption of cloud-first strategies in organizations. What we see now is only the beginning, though. Through 2022, Gartner projects the market size and growth of the cloud services industry at nearly three time the growth of overall IT services.”
SaaS and Cloud businesses are increasingly leveraging AI and Machine Learning platforms to scale their revenue by offering better products and personalized customer experiences. According to Adobe’s Digital Intelligence Briefing, leading companies are more likely to adopt and use AI for Marketing to deliver compelling customer experiences. In the next 18 months or so, by simply looking at companies that have annual revenues between $100 and $150 million, the proportion of AI-driven companies would grow to 24%. The biggest growth factor pushing the adoption of AI within these companies is –Data Analytics, followed by Personalization of On-site content and experiences.
Craig Roth, Research Vice President at Gartner stated –
“The increasing adoption of SaaS applications and other Cloud services impacts the management, dissemination, and exploitation of enterprise content. Organizations are steadily — but not exclusively — shifting their content environments to SaaS. Gartner expects that by 2019, the current enterprise content management (ECM) market will devolve into purpose-built, cloud-based content solutions and solution services applications.”
The expanding #SalesTech landscape https://t.co/FYTBFEPX9W #Sales #CRM #CX #SaaS #AI #Cloud #MarTech #DataAnalytics #PredictiveAnalytics #eCommerce #FinTech #Payments MT @MikeQuindazzi pic.twitter.com/HUqTrXEK9A
— Tamara McCleary (@TamaraMcCleary) October 10, 2018
The AI economy worldwide is projected to reach $36 billion in 2019. By 2022, this industry would more than double to reach $79 billion. The AI-enabled retail industry, discrete manufacturing, FinTech, and Product Experience platforms would be the largest adopters of AI and ML tools for their various Marketing and Sales efforts.
According to McKinsey, Internet Services and Software companies that have grown only by 20% or less annually, it’s most likely to cease existing in the next 3 years. Innovating with AI ML Marketing Could hold the key to sustaining brand reputation, and revenue growth– keys to surviving in the cut-throat competition.
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That brings us to understand how important AI is for Marketing and driving Sales for high-tech businesses, especially those that provide IT Cloud and SaaS products.
But first, let’s define what is AI Marketing!
We already know the evolution of Marketing Technologies and how MarTech RADAR is growing in size and scale. When these MarTech stacks begin to adopt AI applications to boost the ROI and effectiveness in SaaS and Cloud operations, we see AI Marketing bubbling up. Modern B2B and B2C SaaS Cloud enterprise platforms are unique by virtue of many sophisticated components converging together to make things slightly complex for end-customers to fully understand what part of AI is actually working for them.
Therefore, defining AI Marketing becomes very critical to selling to SaaS and Cloud customers.
Artificial Intelligence Marketing is a combination of AI principles and applications directly applied to Marketing concepts with the objective of anticipating customer’s behavior and acquiring a customer by delivering highly contextual, real-time and personalized customer experiences at any stage of the buying journey. Since a large part of these brand-customer interactions occurs online, it is comparatively easy to mitigate and measure AI Marketing results and improve for the next steps.
Strictly sticking to the automated technologies involved, we can define AI Marketing as a branch of Data Science that bridge the gap between Data Aggregation, Management, Analysis, Governance, Privacy, and Execution in Marketing and Sales processes. A large part of AI Marketing operations involves sifting through and analyzing Big Data from countless sources that can only be managed through geared-cycles of Automation, Data Management, Machine Learning algorithms, and Superhuman talent.
SaaS Cloud Transformation in 2019-2022 Depends on Ease and Pace of Customer Data Analytics and AIOps Integration
Provided that Marketing teams have access to a continuous stream of customer data, AI Marketing solutions can boost the sale of IT Cloud and SaaS products. We’ll be addressing all of the details in the content to follow at AiThority.com.
A leading Marketing Cloud company selling to the global B2C market, Selligent Marketing Cloud, reported 60 percent year-over-year (YOY) growth in its global software-as-a-service (SaaS) bookings, particularly bumping sales in North America. A large part of the revenue is attributed to the Company’s expanded product offering toward AI Marketing platform users. This enhanced product line includes AI Marketing tools – Custom Channels, Advanced Journey Components, deeper CRM integrations, and a more robust AI engine. All these empower marketers to deliver flexible Omnichannel campaign orchestration.
Cloud giant and MarTech Customer Experience leader, Oracle, too, charts a very strategic roadmap to grow its customer base via AI Marketing. Oracle offers various development tools and prepackaged AI solutions that help customers accelerate their adoption of AI and Machine Learning (ML). In addition to packaged suites, Oracle is also embedding AI ML into their Cloud services, such as Autonomous Database. Oracle’s AI-based Cloud is used in leading brands, including Outfront Media, NHS, Hertz, CaixaBank, Macty, Accenture and Snap Tech, IDenTV and Daiwa. Oracle’s Mobile Cloud, in particular, has earned a significant reputation in the industry by virtue of its simple adoption and deployment cycle, generating quicker results for chatbot users.
Relatively new players in the industry such as Nudge.ai, People.ai, XenonStack and others in this space are enabling SaaS Cloud customers with extensive tech integrations over their existing IT infrastructure for Marketing and Sales technology. For example, Akira AI Artifical Intelligence Platform enables you to develop Digital Virtual Agents, Chatbots, Predictive agents and cognitive process automation with minimal standardized AI ML operations for multiple data-centers and managed service on the public Cloud. There are many more that provide AI Marketing tools and the numbers are increasing every day.
Other leading players successfully meeting customer needs through AI Marketing applications include IBM, Conversica, Google Cloud, Microsoft, AWS, Genesys, Salesforce, SAP, Adobe, Zendesk, Pegasystems, and Baidu.
We also find leading AIOps and Computing platforms such as NVIDIA, Tencent, HPE, and others joining the club of AI Marketing platforms through cutting-edge tech partnerships, integrations, and collaborations with top MarTech startups.