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Leveraging the Internet of Behavior (IoB) to Boost Customer Loyalty

strategic technology report for 2021. However, the concept of using data to influence customer behavior was developed in 2012 by Göte Nyman, a psychology professor at the University of Helsinki, long before the internet of things took hold.

Gartner defines IoB as an extension of the internet of things, focusing on capturing, processing and analyzing the “digital dust” of people’s daily lives.

Simply put, IoB interconnects IoT, consumer psychology and data analytics. The data is analyzed in terms of behavioral psychology to capture patterns that marketing and sales teams can use to influence customer behavior.

How IoB can Influence Customer Loyalty

Aside from products and services, customer experience has become a significant factor in business success. By understanding customer behavior, businesses can leverage IoB data to influence customer loyalty in various ways.

Personalization

Personalization has the power to transform customer experience. This is reflected in a survey that revealed 76 percent of Americans are more likely to complete a purchase because of a personalized experience.

To take advantage of IoB, companies study insights extracted from collected data and use it to decipher customer behavior; that is, their practices, preferences, habits, needs, wants and more. The company can then leverage this data to offer personalized product recommendations, such as insurance premiums, saving plans, travel destinations, etc.

For example, an insurance company can have users install apps on their phones that collect data on distance traveled, car speed, etc., and optimize their car’s premium based on driving behavior.

Timely Improvement of Products and Customer Services

IoB also makes studying how customers interact with specific services or products easy. This saves companies from time-consuming surveys that are used to determine consumer preferences. The collected data is analyzed to identify pain points and issues of concern. The company can then address the issues before they become significant problems, such as by improving on products and services. This is an excellent way to build trust and confidence in a brand, leading to customer retention.

Behavioral Retargeting

Since companies can access customer preferences, recent activities, likes, dislikes, and location data, they can send real-time notifications to customers about discounts and new offers in stores nearby. They also can track loyal customers and offer them rewards. This kind of retargeting will make customers feel like a business values them and caters to their interests.

Develop a Tailored Marketing Strategy

Insights from IoB data can help tailor marketing strategies to individual customers. For instance, a retail store can offer products or services based on the mood, age or gender of a customer; thereby providing a satisfying experience that will lead to a stronger emotional connection with the brand.

Key Challenges that must be Addressed for the Success of IoB

Despite the opportunities IoB offers, companies must be aware of some key challenges to fully realize its benefits.

  • Privacy Concerns – Although personalization will make consumer lives easier, there is a concern about privacy. Companies must implement strong cybersecurity policies and measures to ensure that customer information is used only for that which a customer has given consent.
  • Convincing Users to Share Personal Data – People might not be comfortable sharing their personal data.
  • Laws and Regulations – Strict regulations around collecting and using personal data, such as the General Data Protection Regulation (GDPR), require companies to comply in order to avoid fines and legal issues.
  • Cybersecurity – As reliance on technology rises, so do cyberattacks. Cybercriminals may access sensitive data on consumer behavior, making consumers susceptible to online scamming and identity theft, among other threats.

Conclusion

Leveraging IoB can provide businesses with a competitive edge and drive revenue growth. Companies seeking continuous success should consider placing IoB at the center of business innovation to create personalized customer experiences. At the same time, they must also examine any challenges that might reduce the effectiveness of IoB.

7 Steps to Start a Business

SWOT analysis, which stands for strengths, weaknesses, opportunities, and threats. After you synthesize and analyze all this data, you’ll have a clear picture of how your business will take shape.

Create a Road Map

You don’t go on a trip without a guide. Starting a business is no different. In your roadmap – or business plan – you’ll want to generate a comprehensive picture of your business, which includes everything from an executive summary and market analysis to a mission statement and financial plan. Other items to include are a marketing plan and an exit strategy. When your business plan is complete, you can share it with potential investors and banks. Here’s a free simple business plan template you can use as a blueprint.

Choose Your Structure

Will you be an LLC (Limited Liability Company), LLP (Limited Liability Partnership), Sole Proprietorship or corporation? There are pros and cons to all of these. In addition, you’ll want to name your business, come up with your DBA (Doing Business As). Then, you’ll register your business, apply for an EIN (Employee Identification Number), and get the right licenses and permits.

Organize Your Finances

Open a business bank account – you’ll need your EIN when you do this. If you sell a product, you’ll need either a bookkeeper or good accounting software. Then determine your break-even point. What are your startup costs? What kind of supplies or professional services will you need? Will you operate out of your garage or rent a space? Here’s the equation to follow: Break-Even Point = Fixed Cost/Contribution Margin.

Fund Your Business

Knowing your break-even point, how will you fund your business? Do you have money saved? Do you have credit cards to use? Do you have cash from friends and family? Small business loans, grants and lines of credit, angel investors, venture capitalists, and crowdfunding are other solid avenues you can explore. Finally, consider buying business insurance to make sure that if something goes wrong, you’re covered.

Market Your Company

After you’ve acquired all the right tools, like accounting software, email hosting, and a credit card processor, you can hang a shingle and get the word out that you’re open for business. Bobby’s Bagels is now serving! You’ll need a website that explains everything you offer, as well as an e-commerce component. Then you’ll want to optimize your site for SEO and create content that is relevant for your target audience. The last step is creating a social media strategy.

All of these steps are high-level. When you’re in the process of gathering everything you need, other details will emerge. Starting a business might be hard work, but it will allow you to become your own boss and, best of all, realize your dream. Remember, you’ll never work a day in your life if you love what you do.

Sources

https://www.forbes.com/advisor/business/how-to-start-a-business/

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How To Use Natural Language Processing To Improve The Efficiency Of Accounting Processes

incorporated NLP into its Audit Command Language to improve contract compliance.

How NLP Can Improve the Efficiency of Accounting Processes

Areas in which NLP helps improve efficiency include:

  1. Forensic Investigations
    When CPAs want to perform forensic investigations, they have to deal with significant amounts of data from documents such as bank statements, transaction data tables, and data found in emails or deposition transcripts. Analyzing all the data as they try to look for specific patterns or gain insights is challenging. However, the application of NLP can be helpful in the investigative analysis process. NLP using algorithms can identify patterns automatically and reduce the time it would have taken to analyze the documents.
  2. Accounting and Auditing
    Auditing is challenging due to the process of reviewing financial statements and ensuring they match regulations and legal standards. Auditors must have excellent analytical and decision-making skills to spot inaccuracies in financial statements. However, NLP helps to optimize the auditing process.
  3. Financial Analysis and Automated Generation of Financial Reports
    NLP can automatically extract financial data from balance sheets, income statements, and cash flow statements. This can cut down on time and error-prone work. At the same time, it can obtain insights from massive financial data sets and financial reports. This enables accountants to make data-driven decisions and quickly identify trends and patterns in the data, hence, making it easy to provide guidance to clients on investments and household finances.
  4. Automated Data Entry
    NLP can be used to extract data automatically from unstructured text documents, including bills and receipts. It also can be used to automate the entry of data from tax documents and input it into accounting systems. This can cut down on time and error-prone work.
  5. Improve Centralized Data Management Solutions
    Incorporating NLP in accounting and procurement helps improve the ability of a centralized data management system to collect and integrate data from different sources. This enables standardization and collaboration. Additionally, the data provided has higher-quality insights. As a result, there is better financial planning and improved risk assessment and management.
  6. Customer Interaction
    NLP can be used to enhance the effectiveness of customer interaction. This is done by automating the procedure for responding to client inquiries, such as concerning invoices, payments, and account balances.

Conclusion

Natural language processing is proving to be a powerful technology that can help improve the efficiency and effectiveness of accounting processes. As it continues to evolve, it will likely become an increasingly important tool for accountants and other financial professionals. Most importantly, these advanced technologies take care of manually reviewing unstructured data. This helps businesses scale and – at the same time – reduce costs.