2020 started with a lot of concern; individuals, businesses, and governments were all thrown into a state of confusion. COVID-19 ravaged the world and there was no known remedy.
2021, however, promises to be a year full of hope. Pfizer and its partner BioNTech have filed for emergency authorization in the US of their Covid-19 vaccine; the advanced trial showed the vaccine protects 94% of adults over 65.
With the view of a remedy at our reach, organizations will start strategizing for 2021. One thing we must learn to live with as a result of the pandemic is home working.
Most business will have to be conducted online as compared to before the pandemic. You will have to deal with the issue of more data that is going to be ferried from one spot to the other.
More than ever before, customer feedback will make a lot of difference in your products and services. You must consider the feelings and comments of your customers if you still want to be relevant and competitive in this “new” business landscape.
The business world is slowly getting used to big data; however, it is the source through which you get your data. One pertinent question you must be ready to answer is, do you have a strategy in place to enable you to gain useful insight into the data even when you have access to it?
Sentiment analysis using product review data
ResearchGate, in a study, revealed that more than 80% of Amazon product buyers trust online reviews in the same manner as word of mouth recommendations. There two channels through which you can get these online reviews: the first is review sites, while the second is social media.
While acquiring the data has been made easy, the data you get from these channels are, unfortunately, unstructured. To make any headway out of the data, you must put in several hours of human labor for structuring and analysis.
However, advancement in technology has made it relatively easy to deploy Natural Language Processing and machine learning into sentiment analysis using product review data. You can use several techniques and complex algorithms such as Linear Regression, Naive Bayes, and Support Vector Machines (SVM) are used to detect user sentiments such as sarcasm, context, and misapplied words.
When you use these techniques, the tool usually separates the reviews into positive, negative, or neutral tags. This will enable you to obtain the relevant insights within minutes.
The insights you have been able to obtain will indicate the needs of your customers and you can then use them for the following:
Discover what your customers like and dislike about your product or service
Sentiment analysis using product review data will not only reveal the feelings of your customers towards your product; you will also understand what they think about your current approach. From this, you will know what improvements you have to implement.
You will have a clear insight into your customers’ mindset and how they interact with each other about your brand. The insights you gain from these will enable you to send content that resonates deeply with your target audience.
Use your product reviews to know your status in the market.
Sentiments about your brand can shift radically and quickly, depending on what’s happening globally. For instance, the Cambridge Analytical Scandal was a big blow to Facebook; you can use sentiment analysis to appropriately monitor your brand’s status and focus on PR campaigns.
You will be able to shift and flex your efforts as quickly as the reviews.
Develop actionable strategies to improve deficiencies
How do you package your product, for instance? Do you believe it has to be bigger or smaller? Can you afford to increase the price, taking into consideration a situation like the COVID-19 pandemic?
When you listen to your customers, you will know the step to take to boost engagement, raise satisfaction, and convert more customers to your brand.
Boost customer conversion rate
While your effort must be geared at getting positive feedback, occasional negative feedback can also be useful. Since they are paying for your product or service, consider your customers as your most honest critics.
Their views are impactful and will help you to acquire new customers if you implement changes. Making adjustments based on insights from customer feedback will help you deliver better customer experiences, products, and services that will keep your customers coming back.
Once they are satisfied, they willingly spread the word to friends and family, bringing in new customers.
Obtain real-time product insights anytime
Feedback through sentiment analysis using product review data is effortless and quick. It can provide you with real-time updates about how customers adjust to any recent change you may make.
Improve service
The more you make positive changes to customer service, the more customers appreciate your gesture and become more loyal. To find out if these changes are necessary, you need to deploy aspect-based sentiment analysis. This will enable you to clinically dissect the problems that may or may not exist in your company.
Conclusion
It’s not just about having data; it’s about carrying out sentiment analysis using product review data. Sentiment analysis will give your brand the actual insight into the mindset of your customers.
Using the information in real-time enables your company to implement the necessary marketing strategies to become relevant and more competitive. You need to constantly watch and analyze the views of your customers because they can change their opinions quickly.
Customers can be erratic, but having a strategy in place that includes sentiment analysis in your digital marketing arsenal will go a long way to improve things.
Image Credit: shutterstock
Alon Ghelber
CMO
Alon is a Tel Aviv-based Cheif Marketing Officer who supports b2b tech startups in capturing customers’ (and VCs’) attention through marketing based on data-driven storytelling.
London-based fintech startup Kennek has raised $12.5 million in seed funding to expand its lending operating system.
According to an Oct. 10 tech.eu report, the round was led by HV Capital and included participation from Dutch Founders Fund, AlbionVC, FFVC, Plug & Play Ventures, and Syndicate One. Kennek offers software-as-a-service tools to help non-bank lenders streamline their operations using open banking, open finance, and payments.
The platform aims to automate time-consuming manual tasks and consolidate fragmented data to simplify lending. Xavier De Pauw, founder of Kennek said:
“Until kennek, lenders had to devote countless hours to menial operational tasks and deal with jumbled and hard-coded data – which makes every other part of lending a headache. As former lenders ourselves, we lived and breathed these frustrations, and built kennek to make them a thing of the past.”
The company said the latest funding round was oversubscribed and closed quickly despite the challenging fundraising environment. The new capital will be used to expand Kennek’s engineering team and strengthen its market position in the UK while exploring expansion into other European markets. Barbod Namini, Partner at lead investor HV Capital, commented on the investment:
“Kennek has developed an ambitious and genuinely unique proposition which we think can be the foundation of the entire alternative lending space. […] It is a complicated market and a solution that brings together all information and stakeholders onto a single platform is highly compelling for both lenders & the ecosystem as a whole.”
The fintech lending space has grown rapidly in recent years, but many lenders still rely on legacy systems and manual processes that limit efficiency and scalability. Kennek aims to leverage open banking and data integration to provide lenders with a more streamlined, automated lending experience.
The seed funding will allow the London-based startup to continue developing its platform and expanding its team to meet demand from non-bank lenders looking to digitize operations. Kennek’s focus on the UK and Europe also comes amid rising adoption of open banking and open finance in the regions.
Featured Image Credit: Photo from Kennek.io; Thank you!
Radek Zielinski
Radek Zielinski is an experienced technology and financial journalist with a passion for cybersecurity and futurology.
As excitement around generative AI grows, Fortune 500 companies, including Goldman Sachs, are carefully examining the possible applications of this technology. A recent survey of U.S. executives indicated that 60% believe generative AI will substantially impact their businesses in the long term. However, they anticipate a one to two-year timeframe before implementing their initial solutions. This optimism stems from the potential of generative AI to revolutionize various aspects of businesses, from enhancing customer experiences to optimizing internal processes. In the short term, companies will likely focus on pilot projects and experimentation, gradually integrating generative AI into their operations as they witness its positive influence on efficiency and profitability.
Goldman Sachs’ Cautious Approach to Implementing Generative AI
In a recent interview, Goldman Sachs CIO Marco Argenti revealed that the firm has not yet implemented any generative AI use cases. Instead, the company focuses on experimentation and setting high standards before adopting the technology. Argenti recognized the desire for outcomes in areas like developer and operational efficiency but emphasized ensuring precision before putting experimental AI use cases into production.
According to Argenti, striking the right balance between driving innovation and maintaining accuracy is crucial for successfully integrating generative AI within the firm. Goldman Sachs intends to continue exploring this emerging technology’s potential benefits and applications while diligently assessing risks to ensure it meets the company’s stringent quality standards.
One possible application for Goldman Sachs is in software development, where the company has observed a 20-40% productivity increase during its trials. The goal is for 1,000 developers to utilize generative AI tools by year’s end. However, Argenti emphasized that a well-defined expectation of return on investment is necessary before fully integrating generative AI into production.
To achieve this, the company plans to implement a systematic and strategic approach to adopting generative AI, ensuring that it complements and enhances the skills of its developers. Additionally, Goldman Sachs intends to evaluate the long-term impact of generative AI on their software development processes and the overall quality of the applications being developed.
Goldman Sachs’ approach to AI implementation goes beyond merely executing models. The firm has created a platform encompassing technical, legal, and compliance assessments to filter out improper content and keep track of all interactions. This comprehensive system ensures seamless integration of artificial intelligence in operations while adhering to regulatory standards and maintaining client confidentiality. Moreover, the platform continuously improves and adapts its algorithms, allowing Goldman Sachs to stay at the forefront of technology and offer its clients the most efficient and secure services.
Featured Image Credit: Photo by Google DeepMind; Pexels; Thank you!
Deanna Ritchie
Managing Editor at ReadWrite
Deanna is the Managing Editor at ReadWrite. Previously she worked as the Editor in Chief for Startup Grind and has over 20+ years of experience in content management and content development.
As Web3 companies increasingly consider leaving the United States due to regulatory ambiguity, the United Kingdom must simplify its cryptocurrency regulations to attract these businesses. The conservative think tank Policy Exchange recently released a report detailing ten suggestions for improving Web3 regulation in the country. Among the recommendations are reducing liability for token holders in decentralized autonomous organizations (DAOs) and encouraging the Financial Conduct Authority (FCA) to adopt alternative Know Your Customer (KYC) methodologies, such as digital identities and blockchain analytics tools. These suggestions aim to position the UK as a hub for Web3 innovation and attract blockchain-based businesses looking for a more conducive regulatory environment.
Streamlining Cryptocurrency Regulations for Innovation
To make it easier for emerging Web3 companies to navigate existing legal frameworks and contribute to the UK’s digital economy growth, the government must streamline cryptocurrency regulations and adopt forward-looking approaches. By making the regulatory landscape clear and straightforward, the UK can create an environment that fosters innovation, growth, and competitiveness in the global fintech industry.
The Policy Exchange report also recommends not weakening self-hosted wallets or treating proof-of-stake (PoS) services as financial services. This approach aims to protect the fundamental principles of decentralization and user autonomy while strongly emphasizing security and regulatory compliance. By doing so, the UK can nurture an environment that encourages innovation and the continued growth of blockchain technology.
Despite recent strict measures by UK authorities, such as His Majesty’s Treasury and the FCA, toward the digital assets sector, the proposed changes in the Policy Exchange report strive to make the UK a more attractive location for Web3 enterprises. By adopting these suggestions, the UK can demonstrate its commitment to fostering innovation in the rapidly evolving blockchain and cryptocurrency industries while ensuring a robust and transparent regulatory environment.
The ongoing uncertainty surrounding cryptocurrency regulations in various countries has prompted Web3 companies to explore alternative jurisdictions with more precise legal frameworks. As the United States grapples with regulatory ambiguity, the United Kingdom can position itself as a hub for Web3 innovation by simplifying and streamlining its cryptocurrency regulations.
Featured Image Credit: Photo by Jonathan Borba; Pexels; Thank you!
Deanna Ritchie
Managing Editor at ReadWrite
Deanna is the Managing Editor at ReadWrite. Previously she worked as the Editor in Chief for Startup Grind and has over 20+ years of experience in content management and content development.
