Latest news with #Entrepreneur
Entrepreneur
13 hours ago
- Business
- Entrepreneur
Why Hiring for Skills Alone Could Be Your Biggest Mistake
Learn how to screen potential employees to fit your company's culture beyond the surface-level requirements. Opinions expressed by Entrepreneur contributors are their own. Professional skills and experience are essential in hiring, but they're only part of the equation. When screening candidates, it's equally important to consider how well someone aligns with your company's culture. This alignment influences employee satisfaction, team collaboration and long term retention. In short, it's the difference between simply filling a role and building a resilient, values-driven organization. In my own hiring process, I look beyond resumes and technical credentials. I pay close attention to how candidates show adaptability, a growth mindset and genuine interest in our mission. I want to know how they work with others, how they respond to change and whether they value integrity and transparency — two of our organization's core principles. One of my go-to questions is how they've handled an ethical dilemma. Their response often reveals far more than a skills test ever could. Your priorities may differ depending on your team's culture, but the approach to identifying fit should follow a similar framework. Here's how to build a hiring process that balances competency with cultural alignment. Related: I've Worked with Hundreds of Entrepreneurs to Scale Their Teams. Here's How to Get the Right People Onboard Understand and define your company culture Before you can screen for culture fit, you need a clear understanding of what your culture actually is. That includes your mission, values, communication norms, leadership style and even how people collaborate day to day. Culture isn't a poster on the wall — it's how work actually gets done. Gallup research shows that just four in 10 U.S. employees strongly agree their company's mission makes them feel their job is important. In other words, candidates are looking for meaning, not just a paycheck. They're researching your company before applying, and if your values aren't visible or clearly defined, they won't know whether to self-select in — or out. During interviews, one question I often ask is: "Can you tell me about a time you had to adapt to a major change at work?" This helps gauge flexibility, resilience and values in action — key indicators of whether a candidate will thrive in our fast-moving environment. Embed culture into your hiring materials Introducing your culture early sets the tone for the entire candidate experience. By weaving your values and workplace norms into job descriptions, career pages and interviews, you attract applicants who resonate with your environment — and deter those who don't. For example, I always outline our mission, values and expectations upfront. We design interview questions around real scenarios our teams face, which allows candidates to demonstrate not only how they think, but how they'd show up day-to-day. Some practical ways to showcase culture in your hiring process include: Sharing employee testimonials on your website or LinkedIn. Describing communication preferences, workplace flexibility and performance expectations clearly in job posts. Using real-life examples in interviews to reflect your values in action. Use open-ended, insightful questions Open-ended questions spark conversation — and surface the deeper qualities that make or break team dynamics. Instead of asking yes or no questions or relying solely on hypothetical situations, let candidates tell real stories about their experiences. This approach helps reveal how they solve problems, navigate conflict, take initiative and collaborate — all things that influence team chemistry and performance. It also allows you to assess communication style and thought process, both critical for a healthy, effective work culture. Related: Your Team Will Succeed Only if They Trust Each Other Be transparent from the start Hiring is a two-way decision. The more transparent you are about the role, the team, and the challenges involved, the more likely you'll find candidates who are genuinely prepared and excited to contribute. If there are tough aspects of the role — unusual hours, evolving responsibilities or shifting team structures — say so upfront. Transparency filters out misaligned candidates early and sets the tone for an honest, trust-based relationship. Ready to break through your revenue ceiling? Join us at Level Up, a conference for ambitious business leaders to unlock new growth opportunities.
Entrepreneur
14 hours ago
- Business
- Entrepreneur
How Tokenization Is Reshaping the Future of Investing
Tokenization is a growing trend in the industry. Here's why it will only reach its potential through utility, not hype. Opinions expressed by Entrepreneur contributors are their own. My investment journey started over 10 years ago. Having invested in over 200 companies since then, I couldn't help but realize the need for a better infrastructure to close my deals. I'd set up a lot of SPVs and tools, and I invested in other providers building tools for investors and fund managers, but I needed fast, efficient and customized platforms. However, the platforms I was looking for did not yet exist, so I adapted by creating my own tools to facilitate a smoother investment experience. This was when I realized that the tools I had developed presented an opportunity that met a significant market demand, specifically in the area of tokenization. With a forecast to reach US$16 trillion by 2030, tokenized assets are tapping into a new generation of finance that extends beyond trading to include accessibility, compliance and more. From there, I found myself leading a venture that had tokenized over US$2 billion worth of assets for 20,000 investors across more than 1,500 funds. Related: The Tokenization Revolution: Reshaping How We Own and Trade Assets More to assets than just trading While the projected value of tokenized assets elicits much excitement, it's crucial to examine what tokenization entails from a utility standpoint, so as not to lose potential in the excitement. Understanding why assets belong on the blockchain needs to go beyond the view of "digital wrappers" that are idle in wallets. Tokenization must be viewed as a key to doors that were once inaccessible, providing opportunities that were once unrealistic. A good example of a door unlocked by tokenization is the tokenized stock exchange, a digital marketplace where traditional shares are converted into blockchain-based tokens. What this unveils is a quicker, more accessible and streamlined trading experience that transcends geographical borders and financial limitations. Tokenized stocks offer investors globally the opportunity to own a slice of U.S. technology leaders, including Apple, Amazon or even a private company like SpaceX, without the need for a U.S. brokerage account. Tokenization will also permit 24/7 trading of public stocks from anywhere in the world. For private stocks, it will unlock significant liquidity for pre-IPO companies, which until now were viewed as very illiquid investments. With geographical borders being removed, financial ceilings are also being lifted as high-priced assets are broken down into smaller units, bringing liquidity to markets that are typically difficult to trade. Take, for example, properties with multi-million-dollar value, and how fractional ownership can enable liquidity from retail investors. Related: Why Your Business Assets Belong on the Blockchain What about compliance? The promise of tokenization, valued at US$16 trillion, is achieved through steps that consider not only utility but also due diligence and precaution. The truth remains that this is a nascent technology with much regulatory ambiguity and global inconsistencies. While the U.S. views digital tokens as securities under the jurisdiction of the SEC, some countries in Asia have yet to develop detailed regulations governing these tokens. Countries are rushing to regulate the space, which drives even more adoption and safety to the industry. As an example, the U.S. Senate is looking to pass the Broker-Dealer Tokenization Act, a bill that would allow broker-dealers to operate in the tokenization space with a well-defined legal framework. This is where one of the most potent elements of tokenized securities comes into play: the ability to directly encode compliance and regulatory requirements into the asset using smart contracts. This embeds compliance in a manner that reduces regulatory overhead, while ensuring market integrity is sustained, and delivers an efficient use of real-world assets among developers and end-users. Exclusivity erodes through utility The norm thus far has been one of exclusive access to primary investment instruments; however, this exclusivity will soon erode due to the advent of tokenization. While we recently saw news about the Circle IPO and other high-ticket crypto projects, the story was yet another case of institutional investors being the early birds that get the worm, as each share was priced at US$31 pre-IPO, opened at US$69, and closed its first day at US$83.23. The arrival of tokenized equities, bonds and yield-bearing instruments is likely to cater to the appetite of both institutional and retail investors, with a lowered entry barrier, broadened access and a shift in opportunities for wealth creation. With tokenization gradually percolating the financial processes of today's economy, it would be no surprise to see the next game changer be access to early-stage gains, such as that of Circle's IPO. Related: How This Finance Guru Created A Breakthrough Financial Service Platform The next generation of finance Moving forward in a world that is growing increasingly tokenized, we're already noticing shifts in the likes of tokenized private credit, with platforms having pushed the volume of on-chain loans beyond US$13 billion in assets under management. This creates an inversion of the old mortgage model, where the token is liquid collateral tracked in real time and the borrower is priced by the pool. Invoices, revenue-share agreements and more can now be cleared in minutes on platforms that are monitored in real-time. The approach of constantly online collateral can also be seen in the corporate world, with tokenized U.S. treasures having reached US$7.2 billion. If this isn't enough, then JPMorgan's first public blockchain treasury trade most definitely provides clear proof of concept. These are some examples that demonstrate how tokenization can unlock the next generation of finance, tapping into the massive potential of this nascent space. The unicorns of tomorrow are those who see in this technology the opportunity to not just tokenize, but to enable the productivity of the assets tokenized in a manner accessible to all with transparency, compliance and security baked into its core.
Entrepreneur
16 hours ago
- Business
- Entrepreneur
Your AI Initiatives Will Fail If You Overlook This Component
Opinions expressed by Entrepreneur contributors are their own. The conversations I am having with CIOs have changed dramatically over the past year. The conversation used to center around digital transformation milestones and cloud migration timelines. Now it's about agents, multi-agent workflows and how to scale AI initiatives beyond proof-of-concept demos. But here's what's becoming painfully clear: Most organizations are trying to build the future of work on infrastructure that was barely able to accommodate yesterday's demands, let alone tomorrow's. As a Field CTO working with organizations at various stages of their AI journey, I'm seeing a troubling pattern. Mature companies rush to implement new agentic technologies, only to discover their underlying systems were never engineered to support the data, velocity, processing requirements or security governance that agentic workflows demand. The results aren't just failed pilots — it's cost, risk and operational drag that compounds over time. Related: Outdated Systems Are Harming Your Business More Than You Realize. Here's How to Modernize Before Disaster Strikes. The agent infrastructure reality Agents and models are fed on data, and without the right structure, network topology and foundational building blocks in place, agents sit around idle, waiting for information. We're not just talking about having data — we're talking about having it in the right format, at the right time, with the right security, transparency and governance wrapped around it. The demands of globalization make this even more complex. When scaling across geographies with bespoke data sovereignty requirements, how is repeatability and consistency ensured when data cannot leave certain jurisdictions? Organizations that put modern infrastructure pieces in place with the goal of facilitating easy scale suddenly find they can onboard customers, move into new markets and launch new product offerings at a fraction of the cost and effort that they used to. Inaction or embracing the status quo leads to what I call infrastructure debt, and it accumulates interest faster than most CIOs anticipate. The operational health diagnostic I use a simple framework to assess organizational readiness: the 60-30-10 model for engineering and software development. In a healthy IT organization, around 60% of resources should focus on "move-forward" incremental feature adds and improved user experience that respond to business unit requirements and customer requests. About 30% is devoted to maintaining current operations in areas like support, bug fixes and keeping existing systems functional. The last 10% needs to be reserved for the huge transformation initiatives that have the potential to 10x the impact of the organization. When I see these ratios skew, particularly when maintenance climbs to 40 or 50% of resources, that is often a systems architecture problem masquerading as an operational issue. You may not be spending more time on maintenance because your code is poorly written, but rather because the underlying infrastructure was never designed to support the current needs, let alone future ones. The systems are getting stressed, things break, shortcuts are taken, and debt just accumulates. If you find yourself climbing the same hill every time you create a new capability — doing the same data transformations, rebuilding the same integrations, explaining why this application can't leverage what you built for that one — it's likely your foundation that needs attention. The multi-cloud strategy evolution Your cloud needs will change as your capabilities mature. You might use amazing AI tools in one cloud while leveraging the partnership ecosystem in another. You may go multi-cloud because different product lines have different performance requirements or because different teams have different expertise. The key is maintaining technology alignment with more open, portable approaches. This gives you the flexibility to move between clouds as requirements change. Sometimes, there's a proprietary technology that's core to what you do, and you accept that as the price of doing business. But wherever possible, avoid lock-in that constrains future decisions. Know who you are as an organization. If you have amazing data scientists but limited Kubernetes expertise, gravitate toward managed services that let your data scientists focus on models rather than infrastructure. If your team wants to optimize every dial and parameter, choose platforms that provide that level of control. Align your cloud strategy with your internal capabilities, not with what looks impressive in vendor demos. Related: How Multi-Cloud Could Be the Growth Catalyst Your Business Needs The data architecture imperative Before implementing any AI initiative, you need to answer fundamental questions about your data landscape. Where does your data reside? What regulatory constraints govern its use? What security policies surround it? How difficult would it be to normalize it into a unified data platform? Historically, data has been sawdust — the inevitable byproduct of work being performed — that then becomes a cost center where you need to pay an ever-increasing amount to store and protect data that becomes increasingly less irrelevant the further you move away from its time of creation. Organizations often discover they've accumulated data over decades without considering its structure or accessibility. That's acceptable when humans are processing information manually, but agents need structured, governed and accessible data streams. Now, data may be an organization's most valuable resource — the more unique or more specialized, the better. The time investment required to prepare your data architecture pays dividends across every subsequent AI initiative. This isn't just about technical capabilities — it's about governance maturity. Can you ensure data flows seamlessly where it needs to go while maintaining security boundaries? Can you coordinate multiple agents accessing different data sources and applications without creating compliance risks? Can you even pull disparate kinds of data from all the file systems, databases and object stores into a single view? Legacy system assessment signals Several indicators suggest your current infrastructure won't support AI ambitions. If you're spending increasing resources maintaining existing systems rather than building new capabilities, that's a structural issue. If every new project requires extensive custom integration work that can't be reused, your architecture lacks modularity. When your sales team loses opportunities because features are "on the roadmap for next year" rather than available now, you're paying opportunity costs for technical limitations. Jeff Bezos once said, "When the anecdotes and the data disagree, the anecdotes are usually right." If you're hearing stories about excessive resource allocation, missed opportunities or customer churn due to system limitations, pay attention to those signals regardless of what your dashboards indicate. The infrastructure transformation approach The rip-and-replace approach has burned many organizations because it assumes everything old lacks value. Modern approaches focus on componentization — addressing system elements individually while maintaining operational continuity. You can migrate functionality without losing capabilities, transitioning from old to new without creating a net loss in what you can deliver to customers. This requires change management discipline and a graceful transition strategy. You're balancing the introduction of new capabilities with maintaining what has been successful. Sometimes, that means a complete rewrite to take advantage of cloud-native technologies, but it requires architected migration of functionality rather than wholesale application replacement. Preparing for agentic scale The organizations that will succeed in the agentic era are those positioning themselves for speed, data accessibility and security without compromising any of these elements. As we move from individual models to agents to multi-agent workflows, the coordination requirements become exponentially more complex. Having data flow seamlessly in the right format at the right time becomes a showstopper requirement. Everything needs integration with the lowest possible latency while maintaining security and compliance boundaries. Cloud platforms that can wrap governance envelopes around everything you're doing help diminish the risk of human error as complexity scales. Organizations that can really excel at this don't just keep up with the Joneses; they are the Joneses. Related: The AI Shift: Moving Beyond Models Toward Intelligent Agents Build for agents, not just apps Your staff are already using AI tools whether your organization has sanctioned them or not. They're uploading data to external services, using models for work tasks and finding ways to be more productive. The faster you can provide them with governed, secure alternatives, the faster you can put appropriate boundaries around how these tools get used. Don't implement AI for the sake of having AI initiatives. Focus on the problems you're trying to solve and the goals you need to achieve. AI is a powerful tool, but it should be applied to address real business challenges, not to check a box for your board. The infrastructure decisions you make today determine whether your AI initiatives will scale or stall. In the agentic era, there's no middle ground between having the right foundation and having a very expensive pile of proofs-of-concept that never delivered business value. Speed, data and security will be the neural system of successful AI implementations. Getting that balance right isn't just a technical challenge — it's a competitive requirement. Join top CEOs, founders and operators at the Level Up conference to unlock strategies for scaling your business, boosting revenue and building sustainable success.
Entrepreneur
16 hours ago
- Business
- Entrepreneur
Why the Future of Business Runs on Invisible AI Infrastructure
AI is no longer just a tool for automation — it's becoming the quiet architecture behind how modern businesses work. Opinions expressed by Entrepreneur contributors are their own. Artificial intelligence has long been seen as a tool for prediction or automation, a forward-looking technology rather than foundational infrastructure. But its deepest impact may not be in doing new things, but in doing old things better: bringing structure where there was once inconsistency. In industries ranging from automotive manufacturing to healthcare, from retail returns to pharmaceutical research, AI is quietly reshaping how work gets done. It standardizes processes that used to rely on human judgment, introduces repeatability where variability once reigned and scales precision across thousands of decisions per day. By turning inconsistent inputs into consistent outputs, AI allows companies to operate with clarity and scale. It often enhances human work, making previously unmanageable processes fully operational. Join top CEOs, founders and operators at the Level Up conference to unlock strategies for scaling your business, boosting revenue and building sustainable success. Structuring quality where inputs vary Automakers contend with supplier variability in parts, while retailers manage diverse product returns; machine learning systems analyze sensor data or images to define consistent, objective standards. BMW's use of AI in its iFACTORY illustrates this shift. By integrating image and acoustic inspection during assembly, they achieve consistent quality among vehicles built with variable components. As structured evaluation replaces reliance on individual judgment, rejection rates decline while overall throughput rises. A similar transformation is happening in the secondhand industry. My company, ATRenew, processes over 90,000 secondhand smartphones daily — highly non-standardized products with diverse conditions. Using this massive volume of real-world data, the company has developed the Matrix Automated Quality Inspection System, which uses computer vision and AI to perform precise, standardized inspections at scale. With over 99% accuracy and labor cost reductions of up to 83%, it brings structure to variability and makes quality assurance repeatable and efficient. This kind of transformation is not limited to manufacturing. In healthcare, AI helps standardize diagnostic imaging interpretations. In agriculture, it evaluates crop conditions from drone footage. The common thread is that AI brings order to complexity. It makes quality assurance scalable, repeatable and reliable. Related: Can Innovation Be Ethical? Here's Why Responsible Tech is the Future of Business Accelerating R&D through structural intelligence In sectors that rely on creativity, structure and scale seem at odds. Yet companies like Unilever are bridging that divide. They build AI digital twins of products and feed them into generative content platforms. These platforms produce personalized visuals and copy for global campaigns. Meanwhile, McKinsey research documents a reduction of up to seventy percent in product development lead times when structured AI methods guide concept iteration. What once required months of testing now completes in weeks. The structure AI brings enables creativity to move faster without compromising coherence. Beyond marketing, structural AI is also reshaping pharmaceutical R&D. By simulating molecular interactions and predicting drug efficacy, AI accelerates discovery cycles while reducing costly trial-and-error approaches. This allows researchers to focus on high-potential compounds and streamline clinical trials. The result is a dramatic increase in innovation velocity, without sacrificing scientific rigor. AI does not replace human creativity. It amplifies it, making experimentation more efficient and scalable. Improving risk and compliance with predictive order Structured insight matters even more in sectors where oversight and trust are paramount. JPMorgan Chase exemplifies this principle through its comprehensive AI strategy. The bank has embedded AI into trading, fraud detection and customer personalization and estimates that these initiatives have the potential to unlock up to $1.5 billion in value. Tools like ChatCFO support finance teams with real-time decision-making, while AI systems simulate the expertise of senior executives to guide internal strategy. Simultaneously, AI tools for risk management and fraud detection operate continuously and at scale. They protect client relationships while supporting regulatory commitments. In retail, Amazon applies similar AI logic to dynamic pricing, adjusting millions of product prices in real time based on demand, inventory and competitor behavior. The result is a financial institution anchored by an algorithmic structure rather than reactive review. Beyond banking, AI-driven compliance solutions are being deployed in healthcare, manufacturing and government. These systems monitor transactions, flag suspicious activity and generate audit trails in real time. They provide transparency, reduce human bias and ensure adherence to evolving regulations. By embedding predictive logic into governance frameworks, AI ensures that organizations stay compliant by anticipating issues before they arise, rather than simply reacting to them after the fact. Optimizing global logistics and resource flow Global logistics is complicated and often unpredictable, but adding structure helps manage that complexity. AI supports smarter planning, quicker responses and better overall performance. It improves route planning, warehouse coordination and last-mile delivery, making supply chains more efficient and dependable. DHL is an example of this change. They're experimenting with all kinds of AI — from self-driving trucks and delivery drones reaching remote spots to smart warehouses that sort and pack stuff faster and with fewer mistakes. They also use AI to predict when machines might break down, so they can fix things before they cause problems. Ultimately, AI transforms a complex, chaotic system into a manageable, scalable network. It helps companies control unpredictability and optimize the flow of goods and resources worldwide with greater precision. Conclusion AI's real promise is not dazzling speed or flashy capability. It is discipline. By transforming fragmented inputs into structured outcomes, AI becomes the backbone that supports every stage of value creation — from inspection to decision to execution. Businesses that see AI as organizational architecture rather than point solutions gain a sustainable advantage. They turn variability into repeatability, complexity into clarity and scattered potential into reliable performance. Leaders aiming to embed AI into operations should start by identifying fragmented workflows. They should apply structural AI to formalize decision logic and scale across functions once early wins are demonstrated. When done correctly, AI becomes part of the enterprise's operating model. It aligns technology with strategy and drives long-term transformation. In that sense, AI shifts from a mere tool to essential infrastructure. Quietly, it rebuilds the core of global operations. As more industries adopt this structural mindset, AI will no longer be seen as a luxury add-on. It will become a foundational element of modern business.
Entrepreneur
19 hours ago
- Business
- Entrepreneur
How to Calmly Confront Bad Reviews and Turn Them Into Growth
What happens when a negative online review shows up like a dark cloud on a sunny day? Here's a blueprint for bouncing back, strategically and emotionally, from the sting of bad feedback online. Opinions expressed by Entrepreneur contributors are their own. We entrepreneurs pour our hearts and souls into our businesses. They are the products of our creative energy, our passion-made manifest. If you're like me, you assume that any customer who takes the time to leave a review wouldn't dream of giving anything less than five stars. You may have even come to expect a steady stream of glowing reviews, so when a customer leaves a one- or two-star review, it can feel like the biggest gut punch. You're not alone in this. I've gone through it personally, and I can tell you, first of all, congratulations! Any business or brand worth its salt will inevitably attract haters. Your business is growing, maturing and scaling to a point where occasional negative feedback is inevitable. That said, the way in which you respond to this feedback is critical. Don't underestimate the damaging effect that bad reviews can have on your business, especially if the complaints are consistent in nature, highlighting problems that need urgent attention. The entrepreneur should offer measured, thoughtful responses to negative reviews but not every complaint is created equal. Here are a few important considerations and strategies for handling the dreaded negative review. Related: Bad Reviews Can Destroy a Small Business. But If You Get One, Here's How to Bounce Back. Is it legit? Some reviews are just bogus. One of your competitors may be trying to undermine your business and thinks that leaving one or more bad reviews is the way to do it. Someone may confuse your business with another. Or, someone may simply be trolling and wants to use your business as the butt-end of an inside joke. These reviews are a fair bit easier to deal with than the ones that have some basis in reality. If you report an illegitimate review to Google or Yelp, they are likely to remove the bogus review from their site. When to respond Most business owners understand that having the option to reply to negative reviews presents an advantage, a chance to mitigate the damage done. But many business owners, unfortunately, do not respond as effectively as they could. Samara Scott-Hunter, host of the Salon Rising podcast, has noticed an off-putting defensiveness in how other business owners often respond to negative reviews and believes there's a better way. After being blindsided by a one-star review that Scott-Hunter felt was deeply unfair, she decided to wait before posting her response. Her cool-off period lasted a whole month, and when she did respond, she made sure she was in the right frame of mind to do so. I remember I was sitting in front of my fireplace. I was just in a really happy place, and it was a Sunday afternoon. I thought to myself, I'm going to respond to that review, because I feel really happy right now. There's wisdom here. If you're like me and many other entrepreneurs, receiving a bad review elicits a highly emotional reaction. In most cases, you don't want that red-hot emotion showing up in your public written response to the review. Nor do you want your hasty reply to be met with subsequent complaints and rebuttals from your critic. Therefore, do what Scott-Hunter did, and allow yourself a cooling-off period. Not only will this improve the quality of your response, but it will also be less likely that you'll bait your critic into an unproductive back-and-forth. Related: 94% of Customers Say a Bad Review Made Them Avoid Buying From a Brand. Try These 4 Techniques to Protect Your Brand Reputation. How to respond You may also invite the customer to reach out to your firm's dedicated support staff. Do this by providing the name, email and phone number for your support personnel in your reply. My company has a dedicated customer experience lead who acts as a first responder in the event of a bad review. For me, the typical format for replying to bad reviews should consist of an apology. I don't think you need to explicitly admit to wrongdoing, but you can express regret for the customer's negative experience. Next, you need to express empathy. Put yourself in the customer's shoes and understand that she may be providing this feedback not to hurt your business but to help it improve. That said, let's not be naïve; as your business grows, you will encounter some customers who are simply impossible to please. These customers may have woken up on the wrong side of the bed, recently lost their pet or a loved one, who knows — but for whatever reason, they're determined to have a go at you online. I advise concluding your response by directing your customer to the relevant support personnel in your organization and assuring them that every reasonable action will be taken to address their complaint. My company has a dedicated customer experience lead who acts as a first responder in the event of a bad review. Her name, email and phone number is provided to the customer along with my response. If possible, you or a member of your support team should reach out to the customer privately and do what you can to address their complaint. If you are successful here, and the customer is satisfied, then you may ask the customer to modify their negative review, perhaps changing one- or two-stars to four- or five. Be careful here, you don't want to come across as pushy, as if you're dead set on getting the customer to change their review or take it down. Approach the situation with a genuine curiosity about the customer's experience, with a real desire to know where things went wrong. Don't ask for any favors without first making it abundantly clear how much you care about their experience with your business or brand and appreciate their feedback. Soliciting and screening reviews When it comes to soliciting customer reviews and containing negative feedback before it goes public, there's no shortage of CRM (customer relationship management) software utilities from which to choose. If you use one or more of these utilities, keep in mind that platforms such as Google and Yelp prohibit the practice of "review gating," which is the selective promotion of positive reviews. A review-gating software may email a recent customer, ask them about their experience and direct them to post a review on Google or Yelp if and only if they've had a five-star experience. While review gating is frowned upon, there's nothing wrong with a business providing great services or products and actively soliciting honest feedback. A winning and ethical attitude for a business is to welcome all feedback and to utilize the negative feedback in pursuit of continuous improvement. Related: How to Remove Negative Reviews Online and Protect Your Online Reputation Try not to take it personally Don't take it personally. Yes, way easier said than done. But as an entrepreneur, it's imperative that you identify the growth opportunity in every setback. Even if you find yourself heartbroken by a string of bad reviews about the business you've worked so hard to build, the right approach is to respond attentively, proactively and with resolve to make all the needed adjustments and improvements. Craft your responses to be impassive, empathetic and constructive. Remember, you can never please everyone all of the time. So, stay open-minded, stay humble and let every challenge sharpen your resolve to build and run a business worthy of your passion. Ready to break through your revenue ceiling? Join us at Level Up, a conference for ambitious business leaders to unlock new growth opportunities.
