MARKETING PLAN FOR AN AI PRODUCT
Executive summary

AI being the future of all technological solutions for various industries, Textit has been formulated with the help of all the advanced technologies that are found in the market today. This paper presents all the necessary pointers related to the marketing strategies that can be adapted to promote the product, along with all the weaknesses and strengths of the product and the scopes for improvement for the same. Besides that, a systematic approach has been taken to critically analyse all the aspects that might affect the production and the market value of the product. The product has been well described with all the necessary justifications, and a specific marketing design has also been presented in this paper.

Table of Contents

Executive summary. 0

Table of Contents. 2

Introduction. 3

Product Analysis. 3

External Market Analysis. 4

Competitors. 6

Internal Analysis. 7

Marketing Objectives. 13

Marketing Strategies. 14

Marketing Mix. 15

Implementation. 16

Conclusion. 16

References. 17

Introduction

• About the company

“Textit” is designed to be a customer support AI product that if launched well in the market may help companies and other businesses with the proper customer supporting tools that are upgraded keeping the current standards of the requirement into consideration. Textit is a product that can be installed into any program be it on a social networking site or a mobile application that is individually owned by a separate company, the optimisation of which will be the responsibility of the original developers of the product. The product aims to fulfil all the emerging requirements of the market, thereby upgrading the system software regularly.

Product Analysis

• Aim of the study and the company

The aim of the study addresses the urgent requirements of a product that is distinctively meant for customer support purposes with all kinds of queries that can be associated with the purchase or selling of a given product. According to Du et al. (2018), studies showed that by the end of the year 2020, almost 80% of the enterprises are going to use chatbots for their business. Thus through such justification alone, one might conclude that the prospects of Textit remain to be a perfect one if appropriately pitched.

• Product and its features

Textit as a product falls under the category of a chatbot that can be optimised and modified based on the requirements of the task. The system can be moulded as per the needs of the clients. The most attractive feature about this product is that it can pass on information that is more detailed and is meant to satisfy the requirements of the customers based on their queries. Reviews and fact-checking mechanisms have been incorporated within the product so that the response that is provided by the AI are majorly accurate.

• Value Proposition

The unique way of selling this product can be its range of accuracy with the information that the product has to provide to its customers. Thus by adding all the necessary changes to customise the product according to the client’s requirements, the value of the product automatically rises from the level that it possesses currently.

• Organisational Constraints

Some of the organisational constraints may involve the limited amount of information possessed by the chatbots of individual enterprises which might ultimately frustrate the customers in the long run.

External Market Analysis

• PESTLE

Table 1: PESTLE analysis

(Source: Created by author)

Political

The issues concerning privacy when a customer logs in to a mobile application have been raised at alarming rates by the general masses. As commented by Jia et al. (2020), this fact has alarmed the government making it crucial for the enterprises to carefully look into the matters of privacy with regards to that of the customers who are involved. Besides that in the year 2019, a specific law under the Personal Data Protection Bill was passed by the parliament ensuring the protection of the customers from various kinds of frauds and misleading activities that take place on behalf of the enterprises.

Economic

In the age of automated services where the customers are dependent on the deliverables sitting back at home, the product has immense capacity to hold on to the target audience or potential customers. According to Yi and Loia (2018), the various kinds of food delivery applications constitute almost 34% of the entire market share. According to Uddin (2019), the amount of revenue earned by those using AI technologies for profit-making cover nearly 9.5 billion US dollar in the year 2018

Social

Chatbots like Textit use one of the more advanced technologies which provide more security to the customers about all the queries and complaints that they have to register based on their purchase Muhulet et al. (2019). Due to the current COVID situation, the software can be further utilised to address all the significant issues about supporting the customer in charity organisations and other healthcare organisations too.

Technological

The advancement in overall technology indicates the utilisation of specific programming that has been included in the software to capture the sight of the client and ultimately, the customers. The AI has been built keeping all the standards of the current market requirements into consideration which makes it a competent one in the market Hao et al. (2019). Technologies that have been used to develop the software includes AI optimised hardware, decision management, natural language generation amongst the others.

Legal

The legal guidelines that are otherwise maintained to protect the best interests of the enterprises are also done in terms of usage of such software that are meant to access the private data of the customers. According to Lu et al. (2018), the IT Act provides the company with some advantages in accessing the personal data of the clients only to fulfil all the required details for the service.

Environmental

According to Huang and Rust (2018), the service provided by an AI can save up to 150 billion US dollars that would otherwise be spent on manual labour invested for the same purpose. Thus this is more cost-effective in the times of emerging competition of making revenues within a short period.

Competitors

• PORTERS

The threat of new entry: The risk of the new entry in this sector is high because of the emerging need for automated service in different enterprises.

Supplier power: The supplier power that is required for this particular product is low because manufacturing this product would highly require workforce as it is majorly based on the technologies.

Competitive rivalry: There is a medium to high range of competitive competition in this sector as there are man AI technologies that are many existing ones that are popular in the current market

Buyer power: Buyer power is high in this aspect because the features that the product offers are somewhat new as compared to the ones that are otherwise found in the market.

The threat of substitute: The risk of substitute is very high as modern technologies are majorly used for these kinds of products.

Figure 1: Porter’s Five forces rule

(Source: Huang and Rust 2018)

Internal Analysis

• Primary Research outcomes

The assessment has been done using the primary research methods, which included conducting surveys and personal interactions with 30 people chosen by random non-probable sampling.

Question 1:
Would you consider addressing your issues to an AI that can access your data with your permission?

Table 2: Survey question 1

(Source: Created by author)

Figure 2: Survey question 1

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Question 2:

Would you rely on the suggestions that are given to you through an AI?

Table 3: Survey question 2

(Source: Created by author)

Figure 3: Survey question 2

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Question 3:

Would you prefer an AI over a telecalling service?

Table 4: Survey question 3

(Source: Created by author)

Figure 4: Survey question 3

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Question 4:

Do you prefer receiving reports through an AI?

Table 5: Survey question 4

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Figure 5: Survey question 4

(Source: Created by author)

Question 5:

Do you agree that AI is the future of customer support services?

Table 6: Survey question 5

(Source: Created by author)

Figure 6: Survey question 5

(Source: Created by author)

Analysis:

Following all outcomes that have been derived through the survey, it can be concluded that the general audience is somewhat sceptical about specific issues that they might face due to using AI technology.

Marketing Objectives

1. Generate information through various kinds of social media platforms to gain knowledge about the latest trends about the industry that the AI is going to be applied on.
2. Keep a track on the effectiveness of the AI technologies and mark the faults that might appear during the utilisation.
3. Properly build a model that has adaptive features and also make a great space for awareness regarding the same.

Marketing Strategies

• Target Market

The target market of this particular product is a healthcare management and other delivery apps that are popularly used by enterprises to provide their services.

• Positioning

The product is mostly a developing software that deals with the emerging necessities of the organisation that it serves. The customer support for this particular product works 24*7, providing additional facilities to the first ten customers or clients who are interested in buying this product.

• SWOT Analysis

Table 7: SWOT Analysis

(Source: Created by author)

Marketing Mix

Product

The product aims to achieve goals about all the discrepancies related to customer support. Besides that, the product can solve the matters concerning the interests of the customers for better reviewing policy for the enterprise.

Price

The price of the product is set according to the current market standards, which are prevalent irrespective of the various industries that exist. However, the price might vary in case of higher demand and supply rates of the current market.

Placement

The targeted placements of this product mostly concern the hospitality sector and the healthcare sector as the services that are presently delivered are mostly coming from these sectors above of work.

Promotion

Separate teams are going to be assigned for the promotional activities for this product, thereby including all the trends and requirements of the current market.

Figure 7: Marketing mix

(Source: Hudson 2018 )

Implementation

The implementation of this marketing strategy has been defined in a very critical and a systematic order keeping into consideration that amount of importance that is devoted to each segment. Thus through proper planning in place, the marketing strategy aims to be a more potent one.

Conclusion

As it can be seen through all the necessary points that are mentioned, Textit is the other alternative of money-saving procedures to earn more profit more sustainably. Along with proper optimisation of the same, the marketing strategy given here proves that the product is capable of solving most of the regular issues that are faced by the enterprises.

References

Du, X., Deng, L. and Qian, K., (2018). Current market top business scopes trend—A concurrent text and time series active learning study of NASDAQ and NYSE stocks from 2012 to 2017. Applied Sciences, 8(5), p.751. As accessed from: [https://www.mdpi.com/2076-3417/8/5/751/pdf]

Hao, Y., Miao, Y., Hu, L., Hossain, M.S., Muhammad, G. and Amin, S.U., (2019). Smart-Edge-CoCaCo: AI-enabled smart edge with joint computation, caching, and communication in heterogeneous IoT. IEEE Network, 33(2), pp.58-64. As accessed from: [https://arxiv.org/pdf/1901.02126]

Huang, M.H. and Rust, RT, (2018). Artificial intelligence in service. Journal of Service Research, 21(2), pp.155-172. As accessed from: [https://www.academia.edu/download/62426469/Artificial_intelligence_in_service_Huang__201820200320-92997-va0ce0.pdf]

Hutson, M., (2018). Artificial intelligence faces reproducibility crisis. As accessed from: [https://www.researchgate.net/profile/Matthew_Hutson/publication/323243757_Artificial_intelligence_faces_reproducibility_crisis/links/5d3d3f6892851cd0468c5943/Artificial-intelligence-faces-reproducibility-crisis.pdf]

Jia, X., Ren, L. and Cai, J., (2020). Clinical implementation of AI technologies will require interpretable AI models. Medical physics, 47(1), pp.1-4. As accessed from: [https://aapm.onlinelibrary.wiley.com/doi/pdf/10.1002/mp.13891]

Lu, H., Li, Y., Chen, M., Kim, H. and Serikawa, S., (2018). Brain intelligence: go beyond artificial intelligence. Mobile Networks and Applications, 23(2), pp.368-375. As accessed from: [https://arxiv.org/pdf/1706.01040]

Muhulet, A., Miculescu, F., Voicu, S.I., Schütt, F., Thakur, V.K. and Mishra, Y.K., (2018). Fundamentals and scopes of doped carbon nanotubes towards energy and biosensing applications. Materials today energy, 9, pp.154-186. As accessed from: [https://dspace.lib.cranfield.ac.uk/bitstream/handle/1826/13644/doped_carbon_nanotubes_towards_energy_and_biosensing-2018.pdf?sequence=4&isAllowed=n]

Uddin, M.N., (2019). Cognitive science and artificial intelligence: simulating the human mind and its complexity. Cognitive Computation and Systems, 1(4), pp.113-116. As accessed from: [https://ieeexplore.ieee.org/iel7/8694204/8948508/08948509.pdf]

Yi, G. and Loia, V., (2019). High-performance computing systems and applications for AI. The Journal of Supercomputing, 75(8), pp.4248-4251. As accessed from: [https://link.springer.com/article/10.1007/s11227-019-02937-z]