Marketers Maximize Growth Using AI to Influence Customer Decisions

Marketers Maximize Growth Using AI to Influence Customer Decisions

Many organizations have accelerated their martech transformation efforts as a result of the Pandemic.

Many organizations accelerated their martech transformation efforts, changing the rules on how they manage customer relationships while exploring new technology solutions, if there was any benefit from the swine flu.

Many of these changes have changed the way marketing is done forever.

These changes have a significant impact. According to a recent survey, half of the marketing leaders think that martech investments could drive revenue growth over the next five years.

The challenge many organizations still face is that their current marketing platform landscape remains fragmented, data sources are vastly different and current budgets don’t allow for massive transformation.

Customer sophistication and expectations were increased as a result of the Pandemic. Expectations were set very high for seamless online experiences by modern brands. A new group of people who may not have interacted with a brand online are now online with your brand.

The result is that prospects and customers expect value when interacting with your brand. They aren’t afraid to switch products, vendors or end service agreements at any point in time. You are competing with the last great experience your customer had in an experience-first world.

There has been a significant increase in customers changing products or cancelling service after the economic downturn, reaching an all-time high of 43%. According to the survey, poor quality customer experience is the most important factor affecting consumer loyalty.

There are a few practical ideas you should think about.

There are Fragmented Martech Stacks that need to be built across.

It is difficult for organizations to consolidate and drive efficiency because of the growing martech platform landscape. Over the past 10 years, the number of marketing platforms has increased from 150 to over 10,000 making it difficult for organizations to decide which platform to invest in.

Industry consolidation has been difficult due to the huge amount of needs in different areas such as web content management, digital asset management, email automation, customer data platforms, journey orchestration engines, personalization engines and omni-channel content platforms Vendors target a wide range of capabilities, complexity and budgets.

It’s a problem for buyers that there is a lot of overlap in the platforms and tools. Purchase decisions tend to center around specific use cases which lead to fragmented decision making. Integration of disparate systems is the biggest obstacle to marketing success.

To avoid this, organizations need to adopt an enterprise martech strategy. Business users need to be able to collaborate and enable multi-dimensional marketing campaigns. Data integration, collection and analysis are important functions. The level of personalization and targeting that can be done with your target audience will be limited if you can’t connect customer data assets.
It’s not practical to avoid martech platforms in most organizations, so you need to build bridges between operational silos and organize the marketing team as a multi-functional unit. To make this happen, orient the teams towards the customer in the way marketing technology is used.

There are 5 insights into the marketing technology landscape.

Understand and map your customer’s journey.

As users evolve how they interact with your brand, the complexity of your customer journeys continues to increase. The path to purchase is no longer linear, making it more difficult to offer personalized service.

Organizations need to think in terms of end-to-end customer journey orchestration and gather deep analytic data at each interaction. In-depth journey maps that consider all the different paths of interactions are critically important. This will give you insights into the issues that may arise during those journeys.

If a customer starts interacting with your brand on their mobile device, migrates to the website, interacts with a chatbot, fills an opt-in email form, adds items to a shopping cart, calls into the service center and ends up in a physical store, all of this could be done These are important for telling the next best action.

A solid data foundation can be implemented with a CDP platform if you map customer journeys. The customer experience will be enriched and new revenue opportunities will be created.

There are expert tips for the martech madness.

It is possible to use a CDP for deep insights and differentiation.

Another important requirement in the enterprise is platform fragmentation. Many of the systems that track and collect customer data don’t take to each other, making it easy for organizations to have over 100 systems.

To feed a variety of downstream customer systems, a unified customer data hub is required. It is paramount to differentiate in the market by providing a seamless, personalized customer experience.

Artificial intelligence and machine learning capabilities have been added to these customer data platforms, which have been around for a long time. They used to just serve as a unified customer data repository.

The platform on which organizations can begin to differentiate is now known as theCDPs. Increasing advertising revenues, reducing content costs, attracting new customers, increasing subscription revenue and reducing Churn can be achieved by connecting data about your customers.

There are many ways to build a CDP. A single, integrated platform that doesn’t require expensive integration across various product silos is provided by a fully integratedCDP platform. A hybrid approach allows organizations to choose which components make the most sense to buy. Flexibility was provided by a fully customized CDP solution.

There is no right way to implement a CDP.

It is possible to create deep customer profiles to deliver highly personalized experiences.

To reach customers with the right experiences at the right moments, it is important to translate the data collected in the CDP.

Understanding the data and its context is a key aspect of personalized experience. Identity resolution is the process of merging user data from different sources and devices into a single profile that tracks behaviors, interests, needs and other meaningful information about your customer.

As customers frequently interact with your brand through a variety of different devices, the challenge in doing this arises. Not all the data can be connected without a CDP, and the quality of the data may be insufficient.

Ensuring the right customer profiles are built is dependent on creating the proper identify resolution rules. The safest way to make sure data integrity is determined matching. It’s tempting to use probabilistic matching as it allows you to build customer profiles without collecting any personally identifiable information, but it can lead to wasted paid media spend and poor experiences for your customers.

The addition of third-party data and cookies should be broken for brands. A deterministic approach will allow you to build high quality customer profiles. The right identity resolution will help you with your marketing.

There is a customer data platform.

Use artificial intelligence to increase your competitive advantage.

Artificial intelligence and machine learning can be used to surface customer insights when you have a unified data platform. Due to the volume and authenticity of the data, the analysis and interpretation of it can be done much faster with the help of artificial intelligence. Self- learning is improving outcomes with the help of the Algorithms.

Many areas of marketing are being applied with the help of artificial intelligence. Customer issues can be flagged before service centers are aware of them with the help of artificial intelligence. Artificial intelligence is driving complicated real-time decisioning to provide relevant next-best actions.

Conversational artificial intelligence platforms like allow businesses to provide on-demand availability to ensure they don’t miss a single business inquiry during or after business hours.

Artificial intelligence is starting to play a bigger role in marketing. There are over 50 platforms that can be used to generate content. is able to generate content for social media. Over 50 different types of content can be created by Wordhero. NeuralText can be used to improve search engine results.

The percentage of companies that have already adopted automation, artificial intelligence, and machine learning is expected to double in the next few years.

There are a lot of different use cases for using artificial intelligence. The ability to automate repetitive tasks and analyze large data sets is very valuable. Artificial intelligence can make marketing budgets go further. Artificial intelligence is not likely to replace the human marketing touch, but it is a very powerful tool to enhance your current team.

Bring it all together to maximize growth.

The marketing leaders know what is at stake. To drive growth through customer acquisition and retention, businesses need to create a personalized customer experience. It is difficult to do given the complexity created by legacy systems and the changing expectations of customers.

To address the need for more data-driven, personalized and effective marketing outcomes, businesses need to tap into the right skills and expertise. It takes a unique set of skills, experience, tools and technologies to tackle this level of complexity.

The future seems bright. Businesses are realizing the benefits of a successful martech transformation by applying best practices and pre-built and tested solutions.

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