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The impact of AI on Customer Relationship Management and the Customer Product Adoption Processes

Futuristic Robot Artificial Intelligence Concept

Dr Myles Wakeham, Mr Carl Wakeham and Ms Maria Hamman

INTRODUCTION TO ARTIFICIAL INTELLIGENCE

Artificial Intelligence (AI) refers to the creation of human-like intelligence that can process, learn, reason, plan, and discern natural language. AI comes in three forms, namely, narrow AI, which we are involved with on a daily basis and which is designed to perform specific tasks within an area (technology with intelligence in a particular domain) and general AI which is not area-specific and can learn and perform tasks anywhere and finally strong AI, which is an artificial super intelligence. Thus far, we have only managed to master narrow AI.

The application of AI uses amongst other technologies natural language processing, speech recognition, robotics, machine learning (ML) and computer vision. An example of AI that you may already be engaging with is SIRI presently available on Apple iPhones who reacts to your voice on command. SIRI will in addition have the ability to “learn” from you as you request information in the future.

According to Carolyn Frantz (Microsoft’s Corporate Secretary), AI will have a major influence on business and will equally have a dramatic impact on jobs. Frantz asserts that in the future, AI will make as much as 75 million jobs disappear in the USA but will be replaced by 133 million more challenging and less repetitive roles. Besides its impact on HR, AI will also influence operations and production, inbound and outbound logistics, Supply Chain Management (SCM), finance and as importantly, marketing.

One of the ways that AI is influencing marketing is with AI marketing assistants like IBM Watson’s Lucy, which is a cognitive problem solver (in contrast with emotional), which acquires knowledge through a determined leaning process. Lucy can be used to determine market segments, develop products, conduct competitive or market analyses, media planning, providing the numeric marketing data needs in writing a marketing plan, assisting with salient information in developing a marketing strategy, creating structured marketing content through a process called Natural Language Generation and so on. According to IBM, Lucy is a powerful tool that marketers “…can use for conducting online research, segmentation and planning and it is so powerful that it can do more in a minute than an entire team of marketers can achieve in months”. Needless to say, the advantage of a marketing assistant like Lucy is that it can digest and analyse literally all the data a company possesses and once it has absorbed all of this data, marketing personnel, according to Watson can ask the following questions, when attempting to solve marketing problems:

  • What are the personality characteristics and attributes of the organisation’s target audience based on a set of predetermined variables?
  • Which segments, towns or regions should be targeted first in order to maximise sales?
  • What content mix should be created for the target audience to maximise the attainment of the marketing and promotional mix objectives? and
  • What is the current competitor activity and how can the organisation use such data to make better marketing decisions specifically within environments like retail channels?

The above are questions that companies need to answer in order to formulate marketing strategies that achieve the marketing goals as set by the enterprise. Lucy and similar AI marketing assistants can, therefore:

  • Create viable segments of a company’s target audience so that it can develop highly personalised content that is designed to appeal to such an audience (target market);
  • Assist in the planning of marketing strategies by interrogating the needs and wants of the target market and how best to maximise sales and profits because of such market intelligence through programmatic targeting as an example.
  • Implement and control the different strategies so that the firm’s objectives may be realised based on data feedback loops put into place; and
  • Create promotion content that is customer-specific so that the organisation’s strategy and promotional mix can be directed specifically at satiating customer and organisational needs and wants.

According to MIT’s Brian Bergstein’s article, which was published in the MIT Technology Review in February 2020, AI as it currently stands:

  • Cannot question decisions so it is basically led by data which could be incorrect;
  • Cannot explain the decisions it has made to qualify or quantify the decision;
  • Cannot understand causation (why things happen following on from an occurrence);
  • Cannot measure psychographic typologies;
  • Cannot reason qualitatively, e.g. how people feel about a brand; and as importantly
  • Cannot understand the concept of, for example, customer loyalty outside of quantitatively ‘crunching’ numbers.

So, from the above points, AI must not be seen as a cure-all for an organisation’s marketing woes but rather a tool to assist the firm in achieving better results in the marketplace.

APPLICATION OF AI IN MARKETING

AI, and systems like Lucy (there are numerous others), will undoubtedly have a huge impact on content marketing as they become more affordable and more popular. They will help companies better understand their audience and the data that are garnered by means of AI will allow marketers to position brands more effectively in the minds of current and future customers and put together more effective strategies so that organisational objectives may be attained. AI will also help them understand what outcomes they can expect by pinpointing accurate customer expectation so that customer-specific targeting can be better planned based upon more reliable forecasting and market intelligence. According to the publication Smart Insights: The Financial Brand (March, 2018), the applications of AI in marketing can be found in Figure 1 below:

AI Marketing

Figure 1: Application of AI in marketing

At present Cookies and other engagement tools follow customers as they interact with websites, products, and applications by providing various data sets that will form a personal ‘ecosystem’ that is programmatically targeted by tools and systems. Here relevance is the key to successful engagement by the consumer with variable pricing bases upon the propensity of interest and purchase.

As can be observed in Figure 1 above, AI can have an explosive impact on marketing throughout the organisation’s relationship with its customers… from demand generation through to the instilling of customer loyalty. It can therefore be used to cement strong and mutually rewarding relationships with customers and help to maximise the lifetime value of the customer. It can have a profound influence on the marketing mix, the consumer adoption model and as importantly Customer Relationship Management (CRM). In essence it can generate awareness, instil interest, create desire and likewise important, facilitate action (AIDA). To further explore the above figure and its content, let us examine the four stages of the application:

  1. REACH: Reach is the initial stage of the buyer’s relationship with the marketer. The idea is to attract potential customers and provide them with an appealing experience that will lead to product trial. Reach commences with smart content curation (selection), which is the stage showing potential customers content relevant to what customers with similar perceived needs are interested in. The second phase is concerned ad targeting, with using programmatic media buying. In other words, by using propensity (tendency) models to effectively target advertisements at the most relevant customers. AI can be used to identify the best media and sites (web pages, areas etc.) to place advertisements. Thirdly, AI generated content writing programmes can select the right customer appeals and then personalised content for targeted prospects. Lastly, AI can be employed for voice search (made use of by Google, Amazon and Apple) to improve structured search traffic by applying digital assistants like Lucy as discussed above.
  2. ACT: The second stage of the customer journey (Act) is intended to grab the customer’s attention and make them aware of a firm’s products and services. It consists of four elements, namely propensity modelling, which uses copious amounts of historical data to make predictions. AI at this juncture helps the marketer to direct customers to the correct messages and locations on websites and to generate outgoing personalised content. The second element is predictive analytics which employs propensity models to process large amounts of data that perform best on selected people at specific stages in the customer buying process, which permits more effective advertisement placements and message content than traditional methods. The third element is predictive analysis. This is implemented to determine the likelihood of attracting customers, predicting what price they are prepared to pay for the offering and equally important to establish what customers are most likely to make repeat purchases. The last element under ‘act’ is lead scoring, which is the process of using predictive analytics to determine how interested the potential customer is and likewise if the lead (potential customer) is worthwhile pursuing in order to covert him or her to a supporting customer.
  3. CONVERT: This is the stage of converting a prospect into a customer. Here the first element is dynamic pricing, which uses AI (machine learning) to develop special offers for potential customers that are most likely to purchase the product or service. By doing this, one can increase sales and maximise profits. The next element is re-targeting, where once again, propensity models are used to determine what content is likely to bring customers back for more. This facilitates the re-targeting of advertisements to make them more effective and customer-centric. Re-targeting is often based on the past customers engagement levels with the initial product offering and interest at the onset. This is frequently based on a series of the same or similar advert / content being sent to the customer and the interaction multiple times and during various traffic and time zones dependent on the brand and category. The third element is web and application personalisation, which once again employs propensity models to personalise a web page or application in the position where the customer is in the purchasing decision making process. Lastly, chatbots use AI to mimic human intelligence in order to interpret customer enquiries and to complete orders. Facebook has created instructions on how to build Chatbots.
  4. ENGAGE: Here we find the stage after a purchase has been made. Where traditionally once a sale was concluded by a salesperson it was customary to make a quick exit before the customer changed his mind. In a modern context however, it is important for a firm to continuously engage with customers in order to build mutually beneficial relationships and to facilitate recurring business and referrals. The first element here is customer service, where AI, though predictive analytics, can be used to determine which customers are most likely to become dormant (stop purchasing) or stop supporting the marketer altogether. With this insight, the firm can reach out to these customers with offers, prompts or assistance to prevent them from churning. The second element is marketing automation. This is when AI is availed to determine when (the best time) to contact customers and what message to use when such contact is made. This facilitates insight into where the firm can improve the effectiveness of its automated marketing. The last element is dynamic emails where predictive analytics using propensity models can use previous custom behaviour to market better targeted offerings via automated email as part of the customer acquisition and retention strategy. The results emanating therefrom can be employed to improve future results by uploading them into the models.

As can be seen from the above, the greatest advantage of AI in marketing is its ability to deliver personalisation in a customer-centric manner and in a large scale. In today’s rather complex world, with numerous channels of distribution, complex supply chains, many customer touchpoints and retail options, customers are being overwhelmed every day with messages on traditional media and on digital/social platforms in novel and unique ways. This random bombardment of marketing messages has already fallen on deaf ears and blind eyes as people want to be treated individually and no as a number. The beauty about AI is that it can help organisations to create consistency and personalised experiences across channels for their customers over the long term.

AI AND ITS IMPACT ON CRM PROCESS

Customer relationship management (CRM) is an approach to managing a company’s interaction with current and potential customers. It uses data analysis about customers’ history with the company to improve business relationships, specifically focusing on customer retention and ultimately driving up sales growth. CRM is also known as a strategy that companies use to manage interactions with customers and potential customers and helps organisations streamline processes, build customer relationships, increase sales, improve customer service, and increase profitability.

The relationship usually starts with the customer becoming aware of the organisation (marketer) via the marketer’s promotions activity or by means of word-and-mouth. When commercialisation of an offering begins, marketers use various aspects of the promotion mix to create product and brand awareness, and thereafter attempt to facilitate product trial and then retrial (repurchase of the offering). By astute and customer-driven marketing, the next step for a marketer is to attempt to generate customer loyalty, then insistency and finally advocacy. By performing the latter, loyal customers become the marketer’s unpaid salespeople in the marketplace. Furthermore, the cost of promoting goods and services to these loyalists and ambassadors reduces as they have already built a strong relationship with both the marketer and its offerings. Finally, being risk adverse, loyalists and advocates, they are nor very price sensitive, which makes them very profitable.

When one examines Figure 1 above, one can see that AI can be used as a strategic tool to acquire new customers, motivate them to try its offerings and then through the use of technology and marketing savvy, retain them by creating long-term relationship based upon mutual trust, understanding and co-dependence. This path to purchase ultimately results in mutual need satisfaction for both the marketer and its customer. So, with a closer understanding of what customers want and need by means of the effective and efficient employment of AI, closer relationships can be forged thereby making it easier for the marketer to manage the mutually binding relationship.

AI AND ITS IMPACT ON THE CUSTOMER ADOPTION PROCESS

The Customer Adoption Process is a 6-step mental process which all customers experience while adopting a product; from learning about a new product to becoming a contented and loyal user of that product. During the process the customer may choose to either decline to buy the product or defer the purchasing thereof. The process of a customer moving from a cognitive state toward the emotional state and finally reaching the behavioural or conative state is another way to explain the Customer Adoption Process. The three stages are as follows:

  1. Cognitive State, which can be defined as being informed and aware of the product and marketer’s existence;
  2. Emotional State, which can be defined as the preferences of the customer; and
  3. Behavioural or conative state, which can be explained as taking the decision to purchase, decline to purchase or defer the purchase.

By examining the three above-mentioned points and Figure 1 above, it can be noted that AI can be used to create awareness of the product and the marketer, influence the decision-making process, reinforce preferences and finally assist in motivating the potential customer to buy. According to Cunningham (2018:178), the customer adoption process has six steps. In Table 1 below, one can observe these steps/stages as well as how AI can influence the process:

 

Table 1: The customer adoption process

Level of adoption

Explanation

Influence of AI in relation to the various AI stages

Awareness

To be created by the marketer in order to inform the customer of the existence of the offering

Reach stage: Reach is the initial stage of the buyer’s relationship with the marketer. The idea is to attract potential customers and provide them with an appealing experience that will lead to product trial. AI uses technology not only to make potential customers aware of an offering and organisation but to use information that has been garnered to ensure that the right message is communicated to the right audience. The strategy at this stage is to alert the potential customer by means of employing the right promotions mix. The idea even at this early stage is to lay the foundation on which future relationships will eventually be built.

Interest and information

The marketer needs to spark interest so that the potential customer is motivated to look for more information

Act stage:The second stage of the customer journey is intended to grab the customer’s attention and make them familiar of a firm’s products and services. The focus here is on stimulating interest so that the potential customer may want to obtain additional information about the offering and organisation. AI at this juncture helps the marketer to direct customers to the correct messages and locations on websites and to generate outgoing personalised content.

Evaluation

Here the customer evaluates the offering against competitor products or product substitutes

Act stage: At this important phase the potential customer seeks as much information as possible so that he or she can make a constructive and well-balanced decision about the offering compared to that which is offered by alternative marketers. During this phase AI employs predictive analytics to determine the likelihood of attracting customers, predicting what price they are prepared to pay for the offering and equally important to establish what customers are most likely to make repeat purchases.

Trial stage

Here the marketer desires the customer to try the product, its features, advantages and benefits. The idea/strategy is that hopefully this will lead to retrial and permanent adoption as a product or brand

Convert stage:This is the stage of converting a prospect into a customer. AI provides dynamic pricing to ensure that the targeted customer can afford the offering and to also re-target where once again, propensity models are used to determine what content is likely to bring customers back for more. This facilitates the re-targeting of advertisements to make them more effective and customer-centric.

Adoption

Here the customer has adopted the product with the marketer’s intent to retrial, loyalty and insistency

Engage stage: Here we find the stage after a purchase has been made. Unlike in the sales orientation stage where sales were transactional in nature, here the focus is on continuously engaging with customers in order to build mutually beneficial relationships and to facilitate recurring business and referrals

Post-adoption behaviour

Should the offering fully appease the needs of the customer then he or she will move from insistency to advocacy where he or she will be willing to recommend the product

Engage stage: The first activity here is customer service, where AI, though predictive analytics, can be used to determine which customers are most likely to become dormant (stop purchasing) or stop supporting the marketer altogether. A customer recovery strategy should be put into place to establish why the customer is not purchasing or why he or she has migrated to competitors. With this insight, the firm can reach out to these customers with offers, prompts or assistance to prevent them from churning. AI also facilitates marketing automation to contact customers at a convenient time and what message to use when such contact is made. This facilitates insight into where the firm can improve the effectiveness of its automated marketing. AI also uses predictive analytics and propensity models to investigate previous customer behaviour to market better targeted offerings via automated emails as part of the customer acquisition and retention strategy. The results emanating therefrom can be employed to improve future results by uploading them into marketing and business models.

Source: Table developed by Wakeham, M., Wakeham. C.N. & Hamman, M.

CONCLUSIONS AND RECOMMENDATIONS: It may be noted in Table 1, that AI can have a profound impact on the way a customer adopts a product, service or retailer. Organisations should therefore use AI as a strategic tool to enhance customer satisfaction, appease the needs of all the stakeholders in the equation and finally enjoy the benefits of a co-dependent relationship. An organisation that does not pursue this strategy will be myopic and will do so at its peril. What an organisation therefore needs to accomplish is aptly depicted in Figure 2 below:

descriptive analysis to prescriptive analytics

Figure 2: Migration from descriptive analysis to prescriptive analytics

Looking at all the analytic options above can be a daunting task. However, luckily these analytic options can be categorised at a high level into four distinct types. No one type of analytic is better than another, and in fact they co-exist with, and complement, each other. In order for a business to have a holistic view of the market and how a company competes efficiently within that market requires a robust analytic environment which includes:

  • Descriptive analytics, which use data aggregation and data mining to provide insight into the past and answer: “What has happened?”
  • Diagnostic analytics, which uses data to provide insight into: “Why did it happen?”
  • Predictive analytics, which use statistical models and forecasting techniques to understand the future and answer: “What could happen?”
  • Prescriptive analytics, which use optimisation and simulation algorithms to advise on possible outcomes and answer: “What should we do?”

AI has a profound impact all of the above types of analytics and should be used in a marketing context for the benefit of all the stakeholders who are involved with the firm.

Robots vs Humans: A compelling story of a powerful and impactful experience

4 - Assegai CaseStudy-01

Ads24 won a bronze in the 2019 Assegai Integrated Marketing Awards for its Food for Thought experiential media campaign. In its third year, the 2019 event was themed Robots vs Humans. This is the case study on how the award-winning activation was conceptualised and rolled out.

To cut through the plethora of activations and events aimed at media agencies and advertisers, Ads24 required a single-minded reason for its existence. It was out of this that Food for Thought was conceptualised, packaged and promoted to inspire and inform targeted individuals about cutting edge developments impacting on their careers and their lives.

In Food for Thought, Ads24 created a brand and a vehicle for giving back in an impactful and memorable way, with a healthy return on effort and investment.

 

Campaign context

In an industry consistently exposed to trends, strategies and knowledge about its field of expertise i.e. media and advertising, Ads24 wanted to create a campaign in which it could influence business and leadership thinking as well as refocus attention to the critical role media owners, brand owners and advertisers play in bridging the gap in the minds of consumers between the now and the future.

The objective of the campaign was to position Ads24 as tribe leaders and critical business influencers within the communication space. It should strengthen business relationships and encourage collaboration through a powerful and impactful experience while reminding key industry advertising leaders about the influential nature of media. Ultimately, the company wanted to grow high-level involvement with top decision makers at media agencies and direct advertiser clients.

The strategy was to ensure Food for Thought stood out from industry clutter via a media industry event that encouraged progressive learning as well as debate around the economic, political, environmental and technological forces shaping the future of business in South Africa. Ads24 had to ensure that the event challenged everyone’s thinking and drove curiosity in an impactful way.

Enormous attention was paid to creating details that provided a full sensory experience. Tactics used to achieve this was through a hyper-personalised and carefully planned invitation process; creating a thought-provoking experience and journey on the day for all attendees; developing an integrated PR plan during and post-event, and maximising social media during and post-event

 

The big idea and its implementation

The world and its economies are experiencing unprecedented times. In every aspect of life, humans face a complex array of sensitive challenges that call for extraordinary responses and creative leadership. There is a massive shift in consumer mentality and media organisations need to proactively adapt to lead this dynamic environment.

Ads24 created an event positioned between a world dominated by artificial intelligence and technology, and one desperate for human connection.

The invitation was issued in the form of a book written by one of the speakers called We Are Still Human, by Brad Shorkend and Andy Golding. The book led to a hidden message in one of its pages, creating engagement and appealing to the natural human inquisitiveness. It also led to another very important feature: the RSVP

For this, Ads24 used hyper-personalisation by using real time data and leveraging of artificial intelligence to deliver a more relevant and surprising experience for the audience. This was done through creating an algorithm as part of the RSVP which predicted a personal surprise for guests to take home, further illustrating the impact of personal consumer centered communication.

 

The event

This event was designed from start to finish to engage every sense and challenge thinking. Every aspect was created to juxtapose the human touch with robotic interpretations. The starting point was a taste bud hack. Each person was invited to take a pill made from the ‘miracle berry’, synsepalum dulcificum. A glass of freshly squeezed lemon juice was then offered. The pill had the ability to mask taste and instead of eye-watering, tart lemon, each person experienced a sweet orange juice flavour.

This served as a metaphor on how we consume news and how easily we are fooled to digest fake news – the very opposite of what we pride ourselves in – the facts, the news and the search for truth.

Each food experience contrasted artisanal, handmade delights with a robotic version of the same. Fresh flapjacks topped with creamy mascarpone cheese and rich berry jam was paired with 3D-printed mascarpone cheese on spirulina-infused flapjacks with pipettes of berry compote. The delicious aroma of fresh-pressed coffee was served side-by-side with coffee cubes.

Each table setting was also designed to represent robots or humans and each attendee was assigned one or the other version of the main meal. Although the outcome of the meal was the same, each component was created by hand or by machine. This created an exciting atmosphere of curiousity and experimentation, culminating in desserts delivered by drones.

 

Content and speakers

Ads24 focused on different aspects of the future by looking at the incredible pace of AI and technology and how it’s reshaping our existence in an increasingly automated economy. With so many areas in which the media and communication is changing, from how we consume news to social media, fake news, hyper-personalisation and programmatic buying, if we don’t keep pace and remain agile to these changes, we face professional extinction.

The line-up included public speaker, entrepreneur and author of the best-selling business book, Legacide, Richard Mulholland, Brad Shorkend, one of the authors of We Are Still Human, and computer scientist, Rapelang Rabana.

Each shared their views on how to stay ahead of the game in a world where the word, ‘phigital’ (physical and digital), is the new normal. Comedian, author and speaker, Don Packett, refereed the debate by posing the questions: Where are we today in the fight between humans and robots? Where will our businesses be by 2030? And, how do we prepare for the journey? We explored the dangers of legacy thinking, how AI can be a tool to advance civilisation and how to be a good human in a technologically shifting world. They raised a few eyebrows, challenged the way we see our industry and our world, and opened the door to a spirited conversation around the future of media in 2030.

 

PR and social media

A series of thought leadership pieces were created based on each of the topics discussed at the event. Every week, for four weeks, a piece was circulated to media. Included in the pieces was a short 30-second video taken at the event relating back to the specific speaker/topic. This insured that when the article was published, readers would have full context to what was discussed/debated at the event.

Key messages were taken and posted on social media with either images or short 30-second videos from the event.

 

Return on investment

Ads24 Food for Thought 2019 provided insight into a world where human connection and artificial intelligence create new opportunities and challenges for the media industry and our world. The event solidified Ads24 as a thought leader among influential media partners and as a competitive media owner in a dynamic and constantly evolving industry.

  • 73 % of those invited attended the event
    • 80% gave us a perfect score for relevant content
  • Organic Social media engagement on the day of the event increased to 6.2% compared to the average rate for May of 1.8%.
  • Content series allowed for further organic reach:
    • Post reach increased by 107%
    • Post engagement increased by 300%
  • Page likes increased by 23%
  • Page views increased by 78%
  • Page followers increased by 14%
  • Average time spent on integrated content: 3 minutes

We achieved an overall PR value average of R6.8 million

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12 Digital Marketing Trends and Innovations For 2020

12 Digital marketing trends and innovations for 2020

Alex Membrillo

Source: https://www.cardinaldigitalmarketing.com/blog/12-digital-marketing-trends-and-innovations-for-2020/

Technology has turned the world into a global village in terms of effortlessly connecting people from all different countries and cultures.

Sharing information is more accessible than it ever has before, making it much easier to generate product awareness or promote your service. And since the internet is such a powerful tool that can be used to generate ROI, investing in digital marketing cannot be ignored. According to eMarketer, “worldwide digital ad spend is predicted to reach over $375 billion by 2021.”

 

 

12 Digital marketing trends and innovations for 2020 B

Therefore, to keep up with your competition then you must keep up with the trends. Take a moment to think critically about the impact of change in technology to your business. And then take advantage of the successful existing business techniques that are out there as well as try to predict where technology is going to go in the future. Your business will grow if you retain and actively reach new customers in a proactive way rather than getting left behind.

However, Cardinal Digital Marketing Agency understands if you don’t have the time to research all these trends and that’s why we’re here to help! Request a free proposal today.

That being said, we’d like to share 12 digital marketing trends for 2020 you should watch out for:

  1. Chatbots Take Off

Many companies will continue using a chatbot, they’re effective software programs that interact with website visitors and customers. Chatbots communicate naturally with people viewing the site and can answer their questions in real-time.

12 Digital marketing trends and innovations for 2020 C

Chatbots either use verbal interactions or chat windows to help web users find what they’re looking for.

Hiring an individual to monitor and communicate with visitors on your website can be expensive, but chatbots save costs by answering questions on your behalf. And subsequently, customers tend to appreciate the personalized service and getting their questions answered.

Additional Benefits of Using Chatbots in Digital Marketing

a). It Saves Time: Unlike humans, a chatbot can provide answers quickly to all kinds of questions. And quick responses mean that customers can make decisions faster.

b). Customer Satisfaction: Unlike humans, the chatbot doesn’t need time to rest. Any time the customer wants information, it’s right at their fingertips. And as the chatbot responds more accurately, your sales conversion rates will increase as well.

c). Good Humor: A chatbot is never moody. You will never hear customers complain about being turned away. They are unbiased, clear, and informative- all the qualities that make your customers feel at ease. 

  1. Use of Private Messaging Apps

As 2020 approaches, many companies will start shifting their focus on how to better utilize private messaging apps. Smartphone apps like WhatsApp, Viber and WeChat are already gaining popularity. And instead of using emails, companies are adopting the use of private apps as well as private messaging groups.

12 Digital marketing trends and innovations for 2020 D

Major brands are already undergoing experiments in monetizing messaging apps and soon enough, customers will be able to pay for products directly through messaging apps. Sending and receiving money will be much easier.

Some applications like WeChat Pay have already made significant progress in making it easier to pay online; WeChat, Venmo, and PayPal users are already getting into the habit of using these types of apps to transfer money to their peers.

  1. Increased Use of Artificial Intelligence

The name “Artificial Intelligence” is exactly how it sounds; it refers to robots or machines having the ability to work like humans. AI uses a combination of different features such as chatbots and voice assistants to quickly find answers.

For instance, Alexa and Siri are voice assistants that provide excellent customer care. Just like a human, they can take orders from the users and work behind the scenes on their behalf.

12 Digital marketing trends and innovations for 2020 E

The AI robot does this by using sensors and human inputs to gather facts about a situation and can also collect/store the search data to improve the user’s future experiences.

Cardinal Digital Marketing even has an AI-powered healthcare marketing software called Patient Stream that allows doctors and healthcare providers to streamline their processes to gain new patients.

  1. Hyper-Targeted Advertising

Companies use digital ads to market their products, but have you ever come across an online ad that was straight up annoying or had nothing to do with you? Not only do online consumers tend to ignore these ads, but they may also end up hating the product and doing everything in their power to stay away from the brand.

Forbes magazine states that because of this overwhelming digital connection, unrelated ads or brands that keep on bombarding people with their irrelevant ads will be disregarded by 49% of people.

But on the other hand, people love great content.

12 Digital marketing trends and innovations for 2020 F

If your brand keeps consistently sends tailored messages, then 36% will respond by buying the product.

Many companies are aware of this trend and are already planning accordingly. And we’re predicting right now that by the year 2020, most companies will be targeting precise audiences and users will only be viewing (and responding to) hyper-relevant ads.

  1. Personalization

Currently, only a few companies are using some form of personalization. And big conglomerates like Amazon are already doing it well.

This household name built their huge internet business by analyzing customers’ behaviors and promoting products based on assumptions and the user’s past purchase history. It showcases products that a person may be interested in by putting forth similar or complementary products in a Recommendations tab, and Amazon found that this upsell tactic works in getting more business.

Personalization is truly the future of digital marketing. And these days, it’s what consumers expect…one study even shows that 79% of consumers feel frustrated if the content their viewing isn’t tailored to them.

12 Digital marketing trends and innovations for 2020 G

According to Gartner, by 2020 at least 90% of online advertisers will start using marketing personalization in some shape or form. And by 2021 there will be a significant increase in fully personalized websites.

Personalization is truly the key to a successful digital marketing campaign in 2020. According to Dale Carnegie,“a person’s name is to that person the sweetest and most important sound in any language.”

12 Digital marketing trends and innovations for 2020 H

This quote says it all in terms of the importance of personalization. This is one of the reasons why companies and marketers address you by your first name whenever you see it in your emails.

It is ultimately the best tool for increasing conversions, and this is the reason why some marketers have been leveraging it for decades to improve their marketing efforts.

One study shows that personalized email campaigns receive 29% higher email open rates and 41% higher click-through rates than traditional emails with no form of personalization.

That means if you haven’t tried out personalization in your digital marketing strategy, then you’re leaving a lot of benefits on the table. Here are some reasons why:

The primary benefit of personalized marketing is having the control to reach a specific group of customers. And by collecting user data from list segments, surveys, or studies, you’re better positioned to create more relevant and effective email campaigns towards targeted audiences based on their buying habits, interests, and behaviors.

For example, if your target audience likes movies and general entertainment, you can embed pop culture references when sending your emails, creating blog posts, or even in your email opt-in forms to deliver a more personalized experience with your content. Hopefully, your audience will appreciate the references and better relate to your brand which will ultimately boost conversions.

  1. New Customers’ Behavior

Along with keeping your existing customers happy, your business should also actively be bringing in new ones as well. Here are some of the ways this will apply to the digital marketing space in 2020 and beyond:

i). Companies will have to work with influencers: Just recently, studies show that about 86% of women have to consult social media before deciding on a product. And this is important- consumers want brands to be honest, friendly, and helpful.

12 Digital marketing trends and innovations for 2020 I

If a brand gets positive feedback from other users, then it’s likely to bring in new users.

ii). Companies will have to focus on video content: A survey done by Wyzowl indicates that about 95% of people have watched a video explaining their products or services.

Through publishing self-made videos, companies more directly engage with their customers by actively providing useful information.

The companies also increase their transparency as customers tend to trust and respect their expertise.

  1. Transparency

Research indicates that companies producing transparent and easy-to-digest information are likely to retain 94% of their customers.

12 Digital marketing trends and innovations for 2020 J

However, how you handle a customer’s private data is vital. In 2018, the GDPR policy was more actively enforced to ensure that companies handle customer data transparently.

This means that there will be more emphasis on this in the future; companies will be required to be completely transparent on what kind of information is being shared to promote their products.

Here’s a Tip on How to Improve Transparency

  • Establish your company’s core values.
  • Make sure that selling is not your only goal.
  • Be an open book to your customers- tell them as much as you can about who they are doing business with.
  • If customers raise some concerns or questions, respond immediately.
  • Be able to take constructive criticism from your customers and respond in a friendly, non-judgmental tone.
  • Create space and encourage people to give different suggestions to help improve your products- facilitate a community around your brand.
  1. Growth in Digital Marketing

TheDrum indicates that by 2020 and through the next few years, the global digital software industry will grow by $74.96 billion.

Consequently, more money will be channelled towards digital marketing. CMO predicts that by the year 2022, around 87% of marketing budgets will be spent on digital marketing.

In fact, this growth in digital marketing will result in a form of marketing referred to as “Agile marketing”, which is a form of marketing that measures how efficiently a brand or company is at achieving its marketing goals and objectives.

An agile marketing team develops winning strategies and theoretical results to inform their stakeholders with the purpose of implementing it quickly. There’s no perfect way to implement agile methodology in your organization (although we’ve found that a hybrid seems to work best).

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Essentially, growth in digital marketing translates into the speed in which new products and services are developed and distributed to meet customers’ needs.

Agile marketing is growing in popularity on social media since brands and marketers have spent the last few years figuring out how to connect and communicate on Facebook, LinkedIn, Pinterest, Twitter, and others.

These social media channels provide enormous insights and data into what types of content works and how best to create it.

Want to leave agile marketing tactics to the experts? Cardinal Digital Marketing Agency can help! Contact us today.

  1. Single Marketing Software Provider

Currently, there are a ton of marketing technology vendors. Just to give you an idea…an average enterprise is using up to 91 marketing cloud services.

This number is overwhelming, which is why many people are switching to one software that syncs every tool. HubSpot has embraced this trend already and others are starting to follow.

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Soon, many enterprises will be using a single marketing software provider.

In case you’re wondering if paying and implementing a marketing software tool is beneficial, here are the benefits:

  • It reduces tedious work: It helps in getting rid of repetitive duties and helps you establish a daily routine.
  • Streamlined marketing efforts: You can keep track of where you’re at in the buyer’s journey with your customers and can communicate with them more effectively.
  • It improves accountability.
  • It makes customer management more manageable.
  • You can document progress much faster and easier.
  1. Next-GEN SEO

Right now, a lot of different changes are taking place in the search engines industry and updates are happening constantly. These changes in the search algorithms have profoundly affected the user’s search results.

Every new algorithm comes with different benefits or problems, depending on how you look at it. Ultimately, the goal of search engines is to help users get specific results that answers their questions.

Therefore, you will see in 2020 and beyond that the quality of search results will improve dramatically.

  1. Voice-Powered Search

As the growth in technology continues to increase rapidly, we will start to see more people using smartphones with voice assistants.

Features like Google, Alexa, and Siri are useful in digital marketing. Voice assistants can search for things, read text loudly, and even voice dictate text messages for you so that you can be hands-free.

Voice search is also essential when using it for your business. It’s helping in the growth of a mobile-friendly movement and adding value to local SEO. Voice search also boosts the use for Artificial Intelligence and prioritizes semantics of searches.

Tips for Power Search Optimization

a). Understand the Language: When people use search engines, many use long sentences with specific keywords. Therefore, to optimize the opportunity to be found in voice search results, use longer keywords and complete sentences (think of what someone would ask a friend about a specific product or service).

b). Be Conversational: When implementing voice search in your website, use an engaging conversational tone when creating the text but remember to use complete sentences and be grammatically correct.

c). Answer Questions: Most people use the internet to get information, whether they are researching a product or service that they need or are trying to Google an answer to try to cheat in a late-night trivia contest. Therefore, think about this when creating content for voice-powered searches. Include any questions that people may ask concerning your products and provide detailed answers.

  1. More Focus on Customer Retention

In the coming years, companies will also start to divert their attention from acquiring new customers to retaining their existing ones.

These companies understand that it takes less money to keep existing customers happy and will channel more effort in the middle and last stages of the buyer’s journey. Because collecting better data and focusing on market segmentation helps save costs.

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Retaining customers helps increase revenue because when you keep your existing customers then they tend to tell their friends and give you referrals. Loyal customers are also likely to be more direct and honest with you regarding any issues or problems, giving you a chance to improve your brand.

Conclusion

If you are operating a business, it’s important to know about the current marketing trends and be able to stay on top of where digital marketing is headed in the future.

And just like Amazon, you can start personalizing your products, using social media to answer questions, and implement video marketing to gain trust and show that you are transparent. Remember, if you are handling any client data then transparency is critical. And there are plenty of marketing software systems that can streamline all your online activities and customer relationships.

AI: Should we be worried?

AI-Should we be worried

Technology has become an integral part of our lives and continues to develop still. Advancements in almost every field (more notably the medical and engineering industries) are largely affected and improved by ongoing technological developments. We are constantly confronted by artificial intelligence these days, whether you know it or not.

For context, Techopedia defines Artificial Intelligence as “an area of computer science that emphasizes the creation of intelligent machines that work and react like humans”.

A little history

Although AI only emerged in our personal lives a few year ago but the concept has been around for decades. The term “Artificial intelligence” was first used by John McCarthy in 1956 during a conference at Dartmouth College in Hanover, New Hampshire. MIT cognitive scientist Marvin Minsky, who attended the conference, became interested in AI’s future. Minsky was later quoted in the book “AI: The Tumultuous Search for Artificial Intelligence” by Daniel Crevier as saying, “Within a generation […] the problem of creating ‘artificial intelligence’ will substantially be solved,”

During the period of 1974–80, after several reports criticised developments in AI, government funding and interest in the field seized and the “AI winter” began. Research was revived again and funded by the British Government in the 1980’s but the industry suffered another setback from 1987 to 1993. Ultimately, research started again in 1997, when International Business Machines Corporation (IBM) created “Deep Blue” – the first computer to beat a chess champion when it defeated Russian grandmaster Garry Kasparov.

Examples of AI in our lives

You may or may not be familiar with Sophia, the social humanoid robot created by Hanson Robotics. Sophia was activated on the 14th of February 2016 but was only introduced to the public in March of that year in Texas, United States. Sophia has received extensive media coverage all over the world and became the first robot to receive citizenship to a country (Saudi Arabia) in 2017.

Sophia was modelled after actress Audrey Hepburn and can display more than 50 facial expressions. It uses voice recognition (speech-to-text) technology and is designed to get smarter over time by analysing conversations and extracting data which allows it to improve responses in the future. Sophia also has cameras in its eyes which, combined with computer algorithms, allows her to see, follow faces, maintain eye contact, and recognize individuals.

You can watch Sophia’s activation and interviews here: https://www.youtube.com/watch?v=HSj4SFBqtJ4

Why Sophia doesn’t yet exist in consumer households, global virtual assistants like Apple’s Siri and Amazon’s Alexa are prime examples of AI that are available to consumers. Additionally, the upcoming trend of self-driving or driverless vehicles showcases the endless possibilities of artificial intelligence.

Of course, not everyone has access to this high-end technology, but AI is more subtle than you think. Common examples of AI in our everyday lives include:

  • Chatbots
  • Google’s predictive searches
  • Product recommendations
  • Mobile banking, and
  • Online maps and directions

Should we be worried?

In 2016 in an interview with CNBC, Sophia was asked if she would like to destroy all humans to which it answered “Okay, I will destroy all humans.” This question was of course anticipated by Sophia’s creators who programmed it to say that as a joke; but it’s scary, nonetheless.

When taken down a notch, loss of employment is another major concern. In an article by  Calum McClelland (https://www.iotforall.com/author/calummcclelland/), A two-year study from McKinsey Global Institute suggests that by the year 2030, intelligent agents and robots could eliminate as much as 30 percent of the world’s human labour. McKinsey also adds that automation will displace between 400 and 800 million jobs by 2030, requiring as many as 375 million people to switch job categories entirely.

Read: How Frightened Should We Be of A.I.? here: https://www.newyorker.com/magazine/2018/05/14/how-frightened-should-we-be-of-ai

Films like Terminator and iRobot tell us that we should be afraid but in actual fact, it’s still too early to tell. Ultimately, the question isn’t whether A.I. and machine automation will change the world, but rather when and how it will happen.

Four big trends driving agility in market research

The IMM Graduate School | Four big trends driving agility in market research webEvery business wants to be ‘agile’ in today’s hyper-accelerated world. But what does that mean? Fast, iterative and adaptive agile research is a non-negotiable for companies moving into the next era of innovation work, says Nick Coates.

The Agile Manifesto was developed by frustrated software developers in 2001. Instead of document driven and heavy processes, it encouraged rapid and flexible responses to consumer input. In recent years, this has stretched to the area of consumer insight, and agility has now become an urgent imperative in the research process.

Fast, iterative and adaptive agile research is a non-negotiable for companies moving into the next era of innovation work.

Instead of following traditional research processes that have not been challenged or revised for many years, researchers need to generate consumer insights quickly, learn from those insights, and then decide on the most impactful next step – depending on where the results take them and not on what has been continued year after year as a matter of ‘best practice’.

Ultimately, agile research should help innovators get to market faster and with better products.

Despite the many strides made with agile research, an Ipsos global survey found that only 24% of consumers felt that brands deliver regular innovations and new products. Innovation remains an elusive concept, with 94% of global executives reporting they are dissatisfied with their organisation’s innovation performance. Researchers need to do better to help facilitate effective innovation for our clients.

Ipsos believes that the journey to agile research will be characterised by four major trends:

  1. Quality and speed.
  2. Social intelligence will play a larger role
  3. Artificial intelligence will help facilitate iteration
  4. Modular innovation approaches will be more popular

Let’s examine each of these trends in detail

  1. Quality and speed

Speed is a key concept of agility. To deliver speed, many types of innovation research – including idea, concept and package testing – have become automated and/or standardised. This is ideal if speed is the only requirement, but these solutions often means research outputs lack quality. Some of the issues that arise from automated solutions include unrepresentative samples, device specific solutions, unproven measures of success and limited analysis and ways of interpreting the data.

Solutions need to be fast and high-quality. For example, idea, concept, and package testing results must be compared to competition to be meaningful and benchmarking is key.

So, how do we ensure quality and speed?

  • Real-time systems in place for assessing respondents. Are they real, are they speeding through the interview, are they providing inconsistent answers? Systems should pick up these faults to correct them in real-time.
  • Device agnostic surveys to maximise coverage and respondent reach
  • Validated success measures should form the basis of all agile idea, concept and package testing. (For example, at Ipsos, we use Relevance, Expensiveness and Differentiation for our rapid innovation testing, measures that have been tested and proven).

We are fortunate enough to have research and development (R&D) to provide device agnostic tools as well as validation of the measures we use in our agile research.

Finally, we expect more diagnostics and guidance from the research solutions that are employed. Solutions should include success drivers, forecasting and profiles, to name some examples that will help to manage innovation portfolios.

  1. Social intelligence and product development

There is huge scope for the role of social intelligence in research practices, one example being product development. It’s fast, it’s flexible and it’s cost-efficient. Social intelligence is already being leveraged to identify innovation opportunities.

While marketers typically rely on surveys, focus groups and desktop research to uncover new trends, social intelligence is becoming a new agile alternative. Social intelligence accelerates innovation because you do not need to ask consumers any questions. Using text analytics, you can analyse large amounts of data and have access to real-time information.

  1. Artificial intelligence will help facilitate iteration

Agile research is not only intended to be fast; it should also be iterative. During rapid concept tests, for example, results from the fieldwork should ideally inform real-time changes to the survey to glean better information based on what has already come up.

Rapid prototyping is another possibly, whereby prototypes are evaluated by consecutive groups of consumers, immediately followed by a work session with R&D to merge the results on-site and in real-time. This then directs the next step – being suggestions from the consumers themselves about further optimisation. This has the potential to happen in one day – merging quantitative rating scales with qualitative explanations.

Iterative approaches such as these are essential to facilitate speed, collaboration, continuous learning and of course, agility. Artificial Intelligence can automate certain research processes, which is why the role of AI is so important. An example would be a programme that creates new questions depending on the replies received from respondents. This allows an intelligent drill down for what non-useful information might otherwise be, should the question not be satisfactorily answered in the first instance.

  1. Modular innovation approaches will become more prevalent

Traditional innovation processes have always followed predefined sequences with yes/no outcomes at the end of each stage. We are starting to see these linear processes giving way to modular approaches. Research and learnings from different sources and studies are merged together and, if appropriate, traditional steps are eliminated because they don’t add value. This agile approach is quicker, easier and more learnings-driven than many traditional market research approaches and, ultimately, will help the marketer get to market faster with a better innovation.

Moving agile to the next level

Agile research promises to help marketers move more quickly, more efficiently and more intelligently than ever before. However, agile research as it exists today is just the beginning of what will be a huge change in how we conduct innovation research and it is something that the research industry should be especially excited about. We expect to see agile research evolve to deliver higher quality research, more (automated) iterative processes and more holistic learnings. The result will be faster, deeper insights that will help marketers achieve greater innovation success.