Digital Transformation

Top 10 Digital Transformation Industry Trends For 2022

As the pandemic situations continued to impact the world since 2020, the Digitization and Digitalization transformation trends from that year sustained their effect in the industry in the year 2021. Most of the digital transformation predictions from last year proved accurate, whereas others didn’t perform well in such hurried times requiring more urgent and strategic needs. So what can we determine from these insights in 2022? Will it still be about enhancing customer experience and data, or will we be seeing new technologies emerging in the industry trends? Well, we will know it all with time; however, there are the top ten digital transformations enlisted here that are sure to arise in the year 2022.

It’s the time of 5G now!

It was forecasted that 5G would be a thing of the mainstream in 2021. The 5g in the sub-6Hz bands is going on track worldwide to support Digitization and Digitalization programs. Complex 5G millimeter wave deployments seek more growth potential with it now. The early deployment of 5G was done on low band 5G frequencies, which were supposed to be twice the faster than LTE; however, they were about marginally quicker than the LTE network. It resulted in observers and consumers feeling less satisfied with this trend of 5G deployment as they didn’t receive the results promised to them.

Nowadays, this trend is changing more, and we can rest assured it will have even faster growth this year. We can expect the acceleration of 5G millimeter-wave deployment in urban and highly populated areas. Also, we will see the expansion of low-band 5G networks to the rural areas.

Remote Work Possibilities Taking a Mega Shift

Remote work was the way of keeping operations of several organizations active during the epidemic period. Now it has continued beyond its limits as well. Many influential organizations in various industries are now offering remote work arrangements to their employees. However, this revolution is undoubtedly facing some inevitable challenges. Not all employees are working remotely yet; the partial volume of employees is still working from office locations. If an organization wishes to transform its operations completely remote, it will require certain technologies that can facilitate seamless collaborations between remote and on-premise employees.

When we look at the studies, we find out only about 8% of the online meeting rooms worldwide were equipped with efficient technologies to handle video call conferencing. The good news is that collaboration companies have noticed this and taken steps towards its improvement.

Innovation in the car industry and smart cities under the hype

Innovation in the car industry leads to the production of intelligent AI-based cars. While most of us still think like Tesla is still leading this revolution, rest assured there are plentiful other players taking initiatives to further this revolution. Also, if we talk about the development of smart cities, we can presume there will be many innovations that will help with maintaining good sustainability. Several technical companies like Plus, NVIDIA, Luminar, and Qualcomm spent the most time last year developing software-based vehicles. We will see further with more improvements in advanced driver assistance systems.

Cities worldwide are also developing their infrastructure to support innovations in the automobile industry. More charging stations are being designed to facilitate smart electric cars. Better public connectivity innovations and other technologies are emerging, and they will continue this cycle over the coming year.

Unvarying focus on AI and automation 

Every day, we generate approximately 2.5 quintillion bytes of data, and this figure is rapidly increasing. But the AI systems we use to manage, regulate, and mine data for insights are only as good as the AI systems we use to manage, control, and mine it for insights. As organizations recognize the value of AI for solving issues better, faster, and at scale, the work that many organizations will continue in 2022 with new use cases for AI will continue to develop.

Keeping these factors under concern, we can anticipate AI to become more omnipresent in everyday work life. It will be more helpful as we will turn the corner from applied analytics and natural language processing to multi-turn conversational AI and inference that will turn our interactions with applications and devices more humane with each upgrade.

The enterprise applications for AI will be more robust now, and this will be backed by exceptional data growth and more influential chips that will help with the acceleration of workload.

In the summary

There will be even more Digitization and Digitalization innovative trends yet to come in the upcoming year. With industries focusing on data, security, AI, and applications, the overarching need to keep data secure will undoubtedly be on the top of the mind. Maybe, we will even get to see quantum computing that has already picked hype in the past years. Regardless, we can say that this year will be a year of technological advancement so let’s wait and see what plays out.

Advanced AI Optimization Research for Marketing & Advertising Campaigns

Advanced AI
AI Optimization Research Process for Marketing & Advertising Campaigns

Traditional marketing modes such as Advertisements have become quite expensive. The modern and effective content marketing channels are overcrowded, making it hard to maintain and coordinate the omnichannel presence. To get through these situations, Advanced AI for Marketing can prove useful in providing solutions to optimize marketing campaigns. Many vast enterprises are already implementing the possibilities offered by various machine learning algorithms. Also, deep neural networks help them select the right advertisement to show to the right customer at the right time.

Top technical companies like Google, Amazon, and Alibaba have been implementing superlative machine learning approaches that can demonstrate their effectiveness at optimizing marketing campaign allocation with improvising customer targeting. Here on this topic, you will find out the latest breakthroughs also, the latest and best practices from the leading enterprises that will provide you with the latest advancements introduced by Advanced AI researchers throughout the previous few years.

Field-aware Factorization Machines in a Real-world Online Advertising System

To predict a customer’s response is amongst the core ML tasks in AI-based marketing. Field-aware Factorization Machines or FMMs have been established recently as modernistic methods to face such situations and, in particular, to win over the competition. In this research, those results have been included that are concluded through implementing this method in a production system. It forecasts click-through and conversion rates for displaying advertisements. It also displays how this method effectively wins modern marketing challenges and is lucrative in real-world predictions.

The Summary of This Paper

FMM methods have demonstrated quite impressive results in numerous competitions. However, it is concluded that the training speed for the algorithms of this method is comparatively too low for a production system. The researchers have introduced two solutions that can help with increased training speed to deal with this situation. These techniques are named Premature Warm Start and A Distributed Learning Mechanism. After conducting experiments with the implementation of these two methods, it was suggested that it helped with an increased number of advertisement displays and increased return on investments while also being fast enough for real-world online marketing campaigns.

Deep Interest Evolution Network for Click-Through Rate Prediction

Click-through rate predictions that help us estimate the possibility of user clicks have become the necessity of the marketing systems. Implementing the CTR prediction model is essential to attain the latent user interest behind the user behavior data. User interests evolve, dynamically accompanying the external environment and internal cognition changes. Even though plenty of CTR models can be used for interest modeling, most of them directly consider the representation of behavior in terms of interest. Also, these models mostly lack modeling for latent interest behind a user’s concrete behavior.

The Summary of This Paper

The research suggests that attaining a user’s interests and dynamics is major to advancing the performance of CTR prediction models. Also, it claims that a user’s explicit behavior doesn’t directly demonstrate their latent interest. Therefore, the researchers establish a Deep Interest Evolution Network that models users’ interest evolving process and accordingly improvises the accuracy of CTR predictions in online marketing campaigns. 

Contextual Multi-Armed Bandits for Causal Marketing

The Advanced AI-based model estimates and optimizes the casual effects of automated marketing. With a focus on casual effects, you ensure better ROI by only targeting the right customers who don’t prefer to take organically. The approach draws on the strengths of the casual interface, uplift modeling, and multi-armed bandits. The model optimizes on casual treatment effects instead of pure outcomes; it also incorporates counterfactual generation within the data collection. The research optimizes over the casual business metric following uplift modeling results. Contextual multi-armed bandit methods help scale to various treatments and perform off-policy policy evaluation of the collected data.

The Summary of This Paper

The marketing team of Amazon suggests a new approach to optimizing advertisement campaigns. The approach draws upon casual interface, uplift modeling, and multi-armed bandits. It allows the targeting of marketing campaigns based on casual outcomes rather than only pure outcomes. Ultimately, this presented model approach helps target only those responsive customers who don’t prefer to respond to marketing campaigns just after seeing them. The research optimization confirms that a focus on casual effects can lead to higher investment returns.

The Conclusion 

Customers expect any marketing campaign to understand their interactions with your product. This understanding works as fundamental for building effective marketing campaigns. Numerous Advance AI tools can automate marketing activities and significantly improvise marketing analytics and insights. These researches are some of the working models that bring the maximum user interactions from implementing AI for Marketing and advertising campaigns. By following this topic, you can rest assured that you are informed about the latest breakthrough in AI optimization research for marketing & advertising campaigns.

Innovative B2B Marketing Strategies for 2022

innovative marketing

Many businesses experienced 2021 as a year of great uncertainty and volatility. These situations were fueled by epidemic situations and continued to affect the ways businesses operate globally. Whereas such uncertainties always pose challenges, they also lead to inevitable innovations. Here on this topic, we are excited to share with readers what the future holds with B2B marketing strategies. As you think about your plans for the upcoming years, consider these innovative B2B marketing strategies.

Digital Transitions 

The epidemics have changed the way a business interacts with its customers. The remote interactions have taken the place of in-person interactions. Therefore, the customers now like dealing with a business at the comfort of their home throughout their entire purchase journey. To fulfill this requirement, they request a high-quality digital experience.

  • Now 90% of B2B customers start their purchase journey by searching for a provider online.
  • Customers are already done with 50% of their purchase process before making their final selection for a potential provider.
  • 73% of the customers are millennial, and about a third of them are the sole decision-makers.

The concept has turned from digital marketing to market in the digital world. If your business has not yet realized your customer’s journey in the complete online manner or you haven’t adopted a digitalized marketing strategy, don’t be late anymore. Doing so is now too vital to ensure your business meets all the expectations of your B2B buyers and your service remains relevant in the digital market world.

The Opportunities

  • Upgrade your business website to meet customers’ expectations with their online journey. The website works as the most prominent tool for any business sale promotion. It is the biggest marketing asset in the current market that works over the internet mostly.
  • Build your website for optimum mobile experience as Google now ranks that website on the top mobile-friendly in the SERPs. Thus, most customers are online for their purchase needs using their mobiles only. So you have to ensure they have the best online experience when they visit your website.
  • Explore and refine digital event opportunities because they will not get off the market anytime soon. There are also hybrid events on the rise that facilitate both in-person and digital options together. 

Customer-Centric Content Prioritization

When you create content that assists your B2B customers in making decisions, you showcase your expertise and values. This shift towards a digital purchase journey makes customer-centric digital content more crucial to ascertain business growth. 

  • 41% of the customers read certain content first before contacting a business.
  • About 70% of customers search and read content directly from a business website.
  • 77% of B2B businesses follow a Customer-Centric Content marketing strategy.
Innovative Marketing Strategies

The customers now prefer to seek more and more content online. If your business fails to showcase its expertise with content marketing strategy, you will miss a grave business growth opportunity. Moreover, strategic and relevant content helps your customers understand that you understand and care about their needs at each step of their purchase journey.

The Opportunities

  • By conducting a content audit, you will understand what sorts of customer needs are being encountered with your current content and where you can make modifications.
  • Make content targeting each step of the purchase journey. Therefore, consider hitting the correct range of content to meet customers’ expectations anywhere in their purchase process.
  • Invest in search engine optimization and marketing to confirm your customers find your content online and make connections with you through it. 

 Ai-Enabled Marketing

Automated B2B marketing initiatives based on AI and machine learning is already benefiting marketers with more effective and faster insights and analytics. AI can assist with everything from targeting the right audience to segmentation, personalization, lead scoring, and content marketing insights.

  • 2/3 of the B2B marketers have been taking steps to evaluate and implement AI for marketing and sales initiatives.
  • AI and machine learning are here to generate more than $1.4 trillion in value by helping marketers solve marketing and sale concerns over the coming three years.
  • The implementation of AI by marketers soared between 2018 to 2020. It took a jump from 29% to 84% within these two years.

Corporate data and analytics have become gravely sophisticated, and they are converging with AI to unlock new customer insights so marketers can drive new marketing opportunities.

The Opportunities

  • Leverage AI’s predictive capabilities for analytics. The use of website cookies to track user activities has now become a customer privacy concern. New regulations resist you from doing so. AI can come in handy to fill that void by utilizing predictive analytics to tell marketers what customers are doing online.
  • AI content strategy tools offer a plethora of customer intent data. It helps target the right audience looking for your products in the market.
  • Custom-made campaigns based on AI can help reach people who conduct specific keyword searches when visiting a website. Therefore, this data can help you target potential customers using custom-made marketing campaigns.

Final Takeaway

The coming time is going to be exciting for innovative B2B marketing strategies. The marketing world is becoming increasingly digital. Also, it’s turning personal too. Hence, AI-driven initiatives provide more meaningful insights and help marketers create more effective and targeted campaigns and strategies. The key lies in figuring out how we can integrate these modern-day trends to lead us to our desired enterprise goals.

Chief Growth Officer (CGO) | The New C-Suite Role

The Chief Growth Officer or CGO is the latest role that is making headlines in the business world. As the title suggests CGO is responsible and accountable for growing the business. However, this is not the first time this C-suite role has been heard. In this blog, you will read about Chief Growth Officer and some essential skills for this particular role.

What is the Chief Growth Officer?

In layman’s terms, the chief growth officer, or CGO, is more than a marketing specialist with blended expertise in marketing, technology, sales, product development, and finance. The CGO is visionary, a natural leader charged with ensuring all departments of the organization are on the same page for achieving strategic objectives. With a vision to keep the entire business forward, a CGO is ideally placed to break or improve the business processes to derive change to benefit the business. Growth is a main responsibility for a CGO, and the right person will find the right path to success.

Essential Skills for CGO

A Chief growth officer should have this basic set of well-honed skills to find innovative ways of advancing a business towards strategic objectives.

Understand the Customer

In the current competitive market conditions, a business needs to enhance customer experience and satisfaction to get an edge over its competitors. Trust building, understanding their expectations, and listening to their needs are vital skills for a CGO. A CGO needs to analyze whether the business is capable of matching customer needs and if not, adjust business strategies accordingly. All these efforts help a business to retain and add new customers for the long-term.

Analyze and Understand Market Trends

One of the critical skills for a chief growth officer is understanding today’s market and future market conditions. The success of their role depends upon finding innovative ways to extract these insights. A CGO needs to understand the emerging market trends and keep customer needs at the center of business activities by optimizing internal processes and reducing costs. Analyzing the market conditions and carrying research to know their business strengths, weaknesses, future business opportunities, and future growth threats. All these business activities help analyze the chief growth officer to plan long-term business growth.

Communicate the Vision

For a CGO, having a great vision of the business is not enough. Without every person working together to achieve a particular goal, it will be hard to be successful. It is no exception every person is dedicated to achieving a goal with a common vision, resulting in better output and performance. CGO must be able to share and communicate his vision to each individual in the organization. It will help everyone understand the value of their work and work in harmony to achieve business growth.

Harness Technology

The advancement in technology has put artificial intelligence at the center of all business success. A CGO needs to work closely with the technology team, analysts and work to evaluate potential partners. It is one of the important skills for a CGO to understand the technology and its limitations. This vital information helps in making smart investments to utilize business growth opportunities effectively.

Improve the Internal Business Processes

The next important skill for a CGO is to simplify the internal processes to serve customers better and increase customer satisfaction. While doing so, it is important to keep in mind the employee’s needs and create a space to improve their productivity. Addressing customer and also employee needs is essential while evaluating and improving the internal processes. They were empowering employees to create innovative solutions and develop an internal process to serve customers better. Improvement in internal processes will help in the long-term retention of employees and customers.

Creating New Opportunities

There is no denying that customer taste and needs change with time, and a product needs to evolve accordingly to cater to them well. It is an important skill for a CGO to conduct market research to analyze the market requirements and change customer needs. A CGO must stay on top of all development processes and improve products or services to create new growth opportunities.

Final Words

There is no doubt that a CGO is a hybrid position designed to get the most out of investments and guide businesses towards sustainable growth as time passes. Even if a CEO in an organization devotes time and energy to grow revenue, there is always a scope to utilize more firepower. The right person in the position of CGO is similar to a second “CEO” focusing on growing business and revenue. For businesses looking to remain successful and innovative, it is time to hire CGO to support CEO efforts and vision, expand the company’s direction to capitalize on new growth opportunities and get those missing growth drivers much needed for the business.

Data Life Cycle in Customer Journey

Data Life Cycle in Customer Experience Journey

When enterprises work on the customer experience, they focus on touchpoints – the single transactional points where a customer interacts with different facets of the business and its various offerings. And it is quite logical as well. These touchpoints represent critical points in the customer life cycle that must be understood and served very well. Data and Technology are the Key enablers to delivering the right and just-in-time experience. Unfortunately, most of our enterprises struggle with disconnected data and not-so-well integrated technology stacks. Even companies that have well-integrated MarTech stacks often struggle with silos of data. As we solve these silos, it is critical that we also understand this concept of Data Life Cycle in Customer Experience Journey. Yes data has it’s own lifecycle!

Understanding every aspect of customer experience and the end-to-end customer journey over a period is vital for businesses. Opting for a data-driven, outside-the-box approach toward customer experience journey helps to put customers at the core of business strategy, thus driving loyalty and revenue. The data generated and sourced from various touchpoints and its analysis can be of different forms. It can be descriptive analytics based on operational data to deducing customer sentiment and behavior from real-time data feeds from all channels and applications. Powered by a range of data analytics tools for operational, streaming, and processing unstructured data, businesses can connect the dots among the key touchpoints to optimize the customer experience journey.

The 4 main types of data that make the Data Life Cycle in Customer Experience Journey are:

  • Intent Data: Collection of behavioral signals from Deep Web that help interpret purchase or renewal intent.
  • Behavioral Data: Data that reveals new insights into the behavior of customers on the web, eCommerce platforms, online games, mobile applications, and IoT.
  • Customer Data: Wide variety of data like demographic, personal information collected by businesses to understand, communicate and engage with customers.
  • Product Usage Data: Data that helps to understand how how-often users interact with your product and their behavior while using the product

Here is a highly recommended article to read about the various technical systems like DMP, CDP and Data Lake to identify what your enterprise needs to connect and use these data types.

Data Life Cycle in Customer Journey

Phase 1: Discovery

Also known as the ‘Reach’ or ‘Awareness’ phase, this phase marks the official beginning of the customer lifecycle. Though it is tough to pinpoint the customer’s exact first contact with the business, it is vital to track the initial touchpoints as accurately as possible to design further marketing and advertising strategies. The data that can be collected during this phase includes the typical search terms, which are bringing people to the business website, the number of new visitors on the website, the point of return of visitors to a website, online reviews, new followers on social media business page, customers’ interaction on social media, data from AdWords and pay-per-click, and the usual prospects and current customer surveys.

Key data from Data Life Cycle in Customer Experience Journey at this stage are:

  • Intent Data is available mostly as anonymous data that is stitched together to make a best guess on the intent of that account or customer. ABM Tools are a very good example in B2B marketing space.
  • Behavioral Data is also available as anonymous data which can be stitched together to a specific anonymous profile.
  • Customer Data is available in case this is an existing customer trying to buy a new product.

Phase 2: Acquisition (Learn/Educate)

The contact initiating phase begins when the company comes on the radar of the prospect. The sole purpose of this phase is to convert the marketing contacts into leads or potential sales contacts. During this phase, it is vital to know the audience and develop messaging strategies according to specific buyers’ persona. The acquisition phase can provide factual data that is easy to analyze. Now, here there are two types of data involved: what and who. What data includes the view sources and referrals, traffic, event, and goal-related data. Who data consists of the business website’s viewers, their landing point after signing up or registering, and how the business website or app is utilized.

Key data from Data Life Cycle in Customer Experience Journey at this stage are:

  • Intent Data is available mostly as known data that is stitched together with behavioral data to make more targeted and personalized experience.
  • Behavioral Data is the best data available at this stage. As the prospect has clearly identified themselves, hence all their web history can be stitched together to understand their journey on your owned media to be more targeted and useful in their journey.

Phase 3: Conversion (Register/Sign up for Trial)

Conversion is the phase where the rubber meets the road. Here the company completes a qualification event when the sale is completed and a prospect is turned into a customer. The pillar on which this phase’s success lies in selling not just the products or services but the relationship. For instance, customers interested in B2B SaaS solutions aren’t merely looking for suppliers but businesses that can become their partners. Here the most critical data is conversion rate, which showcases the percentage of leads that turned into customers. Conversion rate can be tracked in respect to other metrics as well, such as website traffic. Now all prospects will not convert and will abandon the journey. It is the point where the customer lifecycles of such prospects will come to an end. Analyzing the data and finding out what went wrong with these prospects can help tweak the future marketing and strategies.

Key data from Data Life Cycle in Customer Experience Journey at this stage are:

  • Behavioral Data changes from a prospect and marketing behavior to behavior within the product and other customer-facing digital media.
  • Customer Data is officially in play at this stage as we start collecting and processing that data
  • Product Usage Data may be minimally available to inform any recommendations

Phase 4: Support

Once the customer onboarding process is complete and the product utilization is started, it becomes vital to keep all communication lines open if the customer has any issue or query. This is especially critical during the first 90 days because if the customer fails to see or leverage the product or business service’s value, he will likely leave the association. This is what is called churn. In other words, the churn rate is the percentage of existing customers a business is losing and the speed of this loss. To make a customer experience journey rich and seamless, a proactive approach toward support is the need of the hour. This phase involves different data types such as total volume by channel, the average response time, first contact resolution rate, help delay and abandonment rates, and moments of delight. The complete analysis of this consolidated data can help businesses provide their customers the best support experience possible. At this stage product data becomes a major player especially product onboarding and usage data is a critical indicator.

Key data from Data Life Cycle in Customer Experience Journey at this stage are:

  • Behavioral Data and
  • Product Usage Data In product customer behavior data becomes one of the most important but mostly under utilized data at this stage. In most companies, this data lives in silo behind the walls of product teams.
  • Customer Data continues to become mature and can be used to stitch together the best experience to wow a customer.

Phase 5: Expansion

For several companies, upselling and cross-selling are a way of drawing out as much revenue as possible from every client and customer. But this approach can backfire negatively. Instead, the company’s expansion approach should have the goal to help their customers draw out the maximum value of the purchased product or services. This value optimization can be done by creating a customer experience that delivers growing value over a while, developing a natural increase in base-product utilization, a sensible expansion into the additional features and functionalities, and adoption of logical and suitable other products or services of the company. This is the phase where data generated and gathered in the first four stages is consolidated and analyzed to launch an intelligent, insights-driven expansion strategy, one that is designed to deliver the true value. Additional datasets like product data and customer data is of great use at this stage as you identify what is the next best product can offer.

Key data from Data Life Cycle in Customer Experience Journey at this stage are:

  • Behavioral Data
  • Customer Data
  • Product Usage Data

Phase 6: Renew

It would be a bit unfair to call the renewal phase as an individual phase as it is the resultant of a robust customer lifecycle management. Renewals don’t lead a great customer success; rather they are the outcome. If an organization is facing the challenge of lower renewal, it is due to the dissatisfaction in the lifecycle such as issues in onboarding, incomplete adoption of the product, failure of utilizing the complete features that would have brought the desired value to the client, issues with ROI, etc. During this phase, a general customer consensus can be achieved by conducting surveys or through online reviews. Another key performance metric of this phase is churn rate. To sum it up, the data gathered in all the above-mentioned stages, its analysis, and utilization decide the success of the renewal phase. Most importantly, this activity should start few months before the renewal date and not few days before.

Key data from Data Life Cycle in Customer Experience Journey at this stage are:

  • Intent Data is available mostly as known data that is stitched together with behavioral data to make a targeted and personalized experience. Also, data from the deep web can be stitched together to understand if the customer is shopping around and should be offered appropriate offers or solutions to create stickiness.
  • Behavioral Data especially Product Usage Data come together to put together a very customized experience to ensure that the strong value proposition and ROI can be demonstrated to the customer so that they are motivated to renew the service. This data can be combined with Customer Data to offer the best promotions or renewals with no promotions.

Mapping the entire customer experience journey with the right type of data at each phase helps a business understand their customers’ experience and delivery an amazing experience at every touchpoint. To sum up, it is a CONNECTED and COMPREHENSIVE data-driven, outside-in approach to deliver an outstanding, seamless, and rich customer experience that wins both the game of customer experience and business growth. I hope this Data Life Cycle in Customer Experience Journey helps you enable great growth for your enterprise.

You can follow the discussion at https://www.linkedin.com/pulse/data-life-cycle-customer-experience-journey-rohit-prabhakar/