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The debate around AI ROI has gotten loudand, frankly, a little cyclical. One moment, were hearing that AI is the key to exponential growth; the next, that 95% of AI pilots fail. At Addi, weve been able to leverage AI to grow 4x faster while operating at ~2x the profitability of BNPL peers. This year alone, weve saved more than $500,000 from our AI initiatives. But how have we accomplished such strong AI ROI? The difference between performative AI and AI with returns isnt in which model or tool youre using; its how your team is using them. Heres how weve driven genuine AI-native team adoption and built a workflow/data pipeline that actually makes sense. 1) Hire and grow for fluency We run nationwide, admissions-style assessments to find talent in unexpected places (from the Amazon to the Ecuador border), then teach AI-native workflows from day one. From our intern program through our senior leadership, we design our interview process for the AI age. We assign a relevant projectsomething candidates could use AI to help withbut then have a panel interview where they present their project, ensuring that candidates actually know the ins and outs of their work without an AI aid. Our interviews additionally probe into potential candidates own familiarity with AI tools, while our intern cohorts get hands-on with agents and graduate into teams already expecting that fluency. The pipeline is designed to recruit for an AI era from the get-go, versus being an afterthought once already employed. 2) Codify AI-native rituals into culture When it comes to cultivating an AI-native work culture, AI-native is a learned behavior. We invested in extensive AI onboarding and habit-building, pairing every knowledge worker with the right agent or copilot, and encouraging AI usage as the company default. Today, more than 90% of our engineers are weekly active copilot users and ~80% of AI-generated code is accepted. This translates into efficiency gains of up to 60% without increasing headcount. Weve kept our core product engineering team flat for three years while shipping more products. The story here isnt in the savings; its in the deep level of AI adoption weve witnessed among our employees by securing their buy-in, setting expectations for an AI-friendly environment, and offering targeted training. Rollouts fail when AI is treated as a here only if you need it tool. They work when companies rewire rituals around ite.g., code reviews with AI diffs, CX stand-ups that inspect agent transcripts, legal postmortems that include our AIs outputsto normalize the behavior. You might even consider baking AI proficiency into employee reviews. In other words, dont over-index on tools; over-index on culture. That cultural shift is why AI usage at Addi is voluntary yet ubiquitous. 3) Design AI as a colleague Theres a reason our in-house agents have regular names like Addri and Aegis. Every agent at Addi is treated like an employeeone with a clear scope, service-level agreements (SLAs), and metrics. Addris job is first-contact resolution with target customer satisfaction (CSAT); the merchant agent owns KYP throughput and reactivation; Aegis owns escalation latency and evidentiary completeness. Human owners review outputs and tune prompts like they would a new hires playbook, and we always welcome teamwide feedback on how our fellow agentic employees can improve before their next review cycle. Moreover, our AI employees have the same depth of contextual knowledge and understanding that a human employee would, to help them function side-by-side with our team and minimize the frustration that comes with false or limited context. Our agents are tailored to specific roles, not catchalls from an outside vendor that shoehorns a base agent into a wide variety of situations. We ensure theyre trained with high-quality, high-volume, company-owned data. We spent four-plus years building a world-leading data platform, ensuring more than 40 terabytes of data was instantly available as it began building AI agents, giving our digital teammates the best possible training. 4) Invest in the right foundations AI-first isnt what works; data-first is. This is how you ensure your AI colleagues have that employee-like context. More than four years ago (pre-LLMs!) we made the decision to invest in a next-generation data engine that would ensure everything that happened on our platform (from a single text message to a full underwriting analysis) would be stored and could be queried by anyone and anythingtraditional AI models, human analysts, and, yes, even LLMs via vectorization. With a single monorepo and an event-based system that logs everything, we have nearly perfect context: 50 terabytes of clean, searchable data. If you dont own your stack (i.e., control your data and event logs) you will rent your advantage to a vendor. Set your AI-native team up for success by logging everything, and reap the benefits of a database that can be read by humans and AI alike. 5) Celebrate adoption Reward employees usage of AI by celebrating adoption rates, cycle-time reduction, and defects avoided. This year, our AI initiatives saved upwards of $500,000 in annual operating costs. For lean teams where a startups success is their teammates success, these metrics (and transparency) matter. That $500K isnt a bottom-line cut; its $500K back into the pockets of our employees in the form of raises, better benefits packages, and profit sharing. Tie budgets to solved tickets, minutes saved, merchants activatedthen compound wins into subsequent quarters. That mindset of AI gains are your gains is why AI can comfortably power half of our legal and coding throughput, a big chunk of CX, and critical onboarding flows. In Summary Train your people to be AI-native and give them the infrastructure to thrive. The models will change. The muscle you build wont. This approach is how weve been able to launch more products more quickly while maintaining a generally lean teamand its why Im confident the best AI ROI stories are still to come.
Category:
E-Commerce
A decade ago, Ben Collins quit his job as a corporate accountant and started teaching other people how to use spreadsheets more effectively. That move, terrifying as it seemed at the time, paid off brilliantly. Today Collins is the proprietor of an online spreadsheet training academy and the author of a weekly newsletter dedicated entirely to Google Sheets tips. Some 50,000 people subscribe. And yet once again Collins is finding himself facing a sense of uncertainty over what’s nextas the very nature of what a spreadsheet even is enters a dizzying spiral of transformation. “We’ve had more innovation in the last two years than in the 20 before that,” Collins says, referencing the explosion of generative AI technology and its effect on the spreadsheet arena. He isn’t exaggerating. Up until recently, figuring out how to use a spreadsheet to its full potential was akin to learning a foreign language: You had complex formulas, mountains of cryptic functions, and a labyrinth of overwhelming options to decipher. If you were trying to do anything beyond just putting a few pieces of basic data into cells, you practically needed a dedicated spreadsheet expert to figure out how to make it happen. But generative AI is currently reshaping the humble and stubbornly complex spreadsheetwhich, for the most part, seems to be a good thing. After all, no one wants a massive project (or migraine) every time the need for crunching numbers comes up. And while generative AI has plenty of issues both practical and ethical, working within the confines of a single spreadsheet and the black-and-white world of objective data seems to be where those limitations are least troubling, and where AI’s strengths are primed to shine. Still, there’s no escaping that a whole new era is upon us. The biggest question now is how, exactly, it all plays out from hereand whether the need for a spreadsheet expert, be it an independent consultant like Collins or the go-to problem-solver within any office or organization, is bound to evolve or destined to become a relic from a bygone time. The spreadsheet in the AI era When Collins quit his accounting job in 2014 and embarked on a self-made, spreadsheet-centric career path, Anna Monaco was 11 years old. Today, at the ripe old age of 22, Monaco is the founder and CEO of Paradigm, a next-gen spreadsheet service that makes Excel look like an abacus by comparison. Anna Monaco [Photo: Paradigm] The idea behind Paradigm is to take all the complexity and manual effort out of spreadsheets and make managing data simple. Instead of worrying about formulas and functions and formatting, you just upload your dataor even tell the service what sort of data you need and let it source it for you. Paradigm creates your spreadsheet, makes it look slick and professional, and suggests next-step actions to work with the data and put it to practical use. “Manual data entry shouldn’t exist,” Monaco says. “We’re not just a spreadsheet. We’re replacing weeks of labor.” Paradigm and its AI-centric spreadsheet startup contemporariesservices such as Sourcetable, Grid, and Juliusaren’t only replacing labor. They’re also replacing an entire way of thinking about spreadsheets and their role in our lives. And while the reigning spreadsheet-service royalty aren’t exactly rushing to rebuild their long-established interfaces, the same basic principle is already appearing in those environments as well, albeit on a much smaller scale and in a more tacked-on sense. To wit: Microsoft’s AI Copilot is now thoroughly integrated into Excel and can be summoned to help you create formulas and analyze data without needing to do all the traditional heavy lifting. And Google is doing something similar with Gemini in Sheets, now making the chatbot available on demand in any cell with a simple (though extremely familiar-feeling to any longtime spreadsheet user) “=AI” command for summoning its assistance. “You dont need to be an AI or spreadsheet expert to do it,” Google wrote in its announcement of the expansion. Ben Collins [Photo: Ben Collins] Of curse, not everyone is ecstatic about the in-your-face AI in those more traditional spreadsheet setupsespecially people who arent seeking out such features and find their presence can be annoying or even downright dangerous. AI features often insert themselves into situations regardless of whether they’re actively summoned. And while AI-introduced errors within a spreadsheet generally seem at least a little less egregious than generative AI at its most hallucinogenic, Microsoft is warning that Copilot is best suited for “scenarios where deterministic accuracy is not required” and not for “any task requiring accuracy or reproducibility” (ouch). So where, then, does all of this leave the spreadsheet expertsfolks like Ben Collins who have spent decades building up deep knowledge in the inner workings of the spreadsheet and all the logic around it? The answer, it turns out (much like the conventional spreadsheet itself) is complicated. Expertise, reinvented Collins sees what’s happening with spreadsheets at Google and Microsoft, and at the more ambitious scrappy spreadsheet startups like Paradigm, as an unambiguous net positive. “All the AI stuff is democratizing spreadsheets in the same way it’s doing for coding,” he says. “It lets more people have access to those insights and that knowledge rather than just the technically savvy crowd.” And yetlike in so many other industries right nowit’s impossible to avoid questions over the effects this shift could have on the future. We’re all living through a transition where some say AI is taking away countless jobs and others insist it’s creating as many as it’s killing, or at the very least just changing what types of roles matter. As with many careers, the only real certainty surrounding spreadsheet-related professions right now is a complete and utter sense of uncertainty. Collins, for his part, remains upbeat. He says he’s seen a shift in the sort of information knowledge workers are seeking around spreadsheets but that he continues to see a strong demand for a deeper understanding of the tools themselves and the data philosophies around them. “There’s still a need to have a foundation of knowledge and an understanding of how these things work,” Collins says, even if only so you can figure out how to ask an AI assistant for what you need and then assess the quality of what you’re given in return. “It’s less emphasis on pure syntax and the mechanics and more [on] how we can use these tools at a higher level and be more effective,” he adds. Collins also notes that for all the buzz around newer AI-centric spreadsheet tools, the vast majority of peopleand businessesare so deeply engrained in the Google or Microsoft ecosystems and so familiar with those environments and the security assurances around them that they won’t be making a major night-and-day change anytime soon. Even if AI does slowly seep its way into their work within those domains. That’s a point Monaco is well aware of. She sees Paradigm as being less of a play at pulling the masses away from Sheets or Excel and more of a forward-looking option for a different generation of businesses. “There’s a new way that companies are being built, where smaller teams are commanding a lot more resources and doing a lot more powerful things with the resources they have,” she says. “Paradigm is building for that future.” One thing she and Collins agree on is that the need for expertise isn’t going anywhere. Monaco says she’s already seeing the emergence of what she calls “Paradigm consultants”people who specialize specifically in supporting the tool she created and helping users figure out how to get the most out of it. “It’s a different expertise,” Monaco says. “There’s still a huge value in becoming a power user and knowing how to harness these tools. There’s an even bigger value now that these tools are more powerful.” Collins also envisions his role evolving. And he is 100% up to the challenge of adapting right alongside that. “The need for training is as strong as ever,” he says. And that, it seems, is something where a genuine human touch and the type of critical-thinking perspective AI can’t entirely emulate remainsfor the current moment, at leastas important as ever.
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E-Commerce
For decades now, we have been told that artificial intelligence systems will soon replace human workers. Sixty years ago, for example, Herbert Simon, who received a Nobel Prize in economics and a Turing Award in computing, predicted that machines will be capable, within 20 years, of doing any work a man can do. More recently, we have Daniel Susskinds 2020 award-winning book with the title that says it all: A World Without Work. Are these bleak predictions finally coming true? ChatGPT turns 3 years old this month, and many think large language models will finally deliver on the promise of AI replacing human workers. LLMs can be used to write emails and reports, summarize documents, and otherwise do many of the tasks that managers are supposed to do. Other forms of generative AI can create images and videos for advertising or code for software. From Amazon to General Motors to Booz Allen Hamilton, layoffs are being announced and blamed on AI. Amazon said it would cut 14,000 corporate jobs. United Parcel Service (UPS) said it had reduced its management workforce by about 14,000 positions over the past 22 months. And Target said it would cut 1,800 corporate roles. Some academic economists have also chimed in: The St. Louis Federal Reserve found a (weak) correlation between theoretical AI exposure and actual AI adoption in 12 occupational categories. Yet we remain skeptical of the claim that AI is responsible for these layoffs. A recent MIT Media Lab study found that 95% of generative AI pilot business projects were failing. Another survey by Atlassian concluded that 96% of businesses have not seen dramatic improvements in organizational efficiency, innovation, or work quality. Still another study found that 40% of the business people surveyed have received AI slop at work in the last month and that it takes nearly two hours, on average, to fix each instance of slop. In addition, they no longer trust their AI-enabled peers, find them less creative, and find them less intelligent or capable. If AI isnt doing much, its unlikely to be responsible for the layoffs. Some have pointed to the rapid hiring in the tech sector during and after the pandemic when the U.S. Federal Reserve set interest rates near zero, reports the BBCs Danielle Kaye. The resulting hiring set these firms up for eventual workforce reductions, experts saida dynamic separate from the generative AI boom over the last three years, Kaye wrote. Others have pointed to fears that an impending recession may be starting due to higher tariffs, fewer foreign-worker visas, the government shutdown, a backlash against DEI and clean energy spending, ballooning federal government debt, and the presence of federal troops in U.S. cities. For layoffs in the tech sector, a likely culprit is the financial stress that companies are experiencing because of their huge spending on AI infrastructure. Companies that are spending a lot with no significant increases in revenue can try to sustain profitability by cutting costs. Amazon increased its total CapEx from $54 billion in 2023 to $84 billion in 2024, and an estimated $118 billion in 2025. Meta is securing a $27 billion credit line to fund its data centers. Oracle plans to borrow $25 billion annually over the next few years to fulfill its AI contracts. Were running out of simple ways to secure more funding, so cost-cutting will follow, Pratik Ratadiya, head of product at AI startup Narravance, wrote on X. I maintain that companies have overspent on LLMs before establishing a sustainable financial model for these expenses. Weve seen this act before. When companies are financially stressed, a relatively easy solution is to lay off workers and ask those who are not laid off to work harder and be thankful that they still have jobs. AI is just a convenient excuse for this cost-cutting. Last week, when Amazon slashed 14,000 corporate jobs and hinted that more cuts could be coming, a top executive noted the current generation of AI is enabling companies to innovate much faster than ever before. Shortly thereafter, another Amazon rep anonymously admitted to NBC News that AI is not the reason behind the vast majority of reductions. On an investor call, Amazon CEO Andy Jassy admitted that the layoffs were not even really AI driven.” We have been following the slow growth in revenues for generative AI over the last few years, and the revenues are neither big enough to support the number of layoffs attributed to AI, nor to justify the capital expenditures on AI cloud infrastructure. Those expenditures may be approaching $1 trillion for 2025, while AI revenuewhich would be used to pay for the use of AI infrastructure to run the softwarewill not exceed $30 billion this year. Are we to believe that such a small amount of revenue is driving economy-wide layoffs? Investors cant decide whether to cheer or fear these investments. The revenue is minuscule for AI-platform companies like OpenAI that are buyers, but is magnificent for companies like Nvidia that are sellers. Nvidias market capitalization recently topped $5 trillion, while OpenAI admits that it will have $115 billion in cumulative losses by 2029. (Based on Sam Altmans history of overly optimistic predictions, we suspect the losses will be even larger.) The lack of transparency doesnt help. OpenAI, Anthropic, and other AI creators are not public companies that are required to release audited figures each quarter. And most Big Tech companies do not separate AI from other revenues. (Microsoft is the only one.) Thus, we are flying in the dark. Meanwhile, college graduates are having trouble finding jobs, and many young people are convinced by the end-of-work narrative that there is no point in preparing for jobs. Ironically, surrendering to this narrative makes them even less employable. The wild exaggerations from LLM promoters certainly help them raise funds for their quixotic quest for artificial general intelligence. But it brings us no closer to that goal, all while diverting valuable physical, financial, and human resources from more promising pursuits.
Category:
E-Commerce
The value of higher education has been on a steady decline for Americans over the past 15 years. According to a September Gallup poll, only 35% of U.S. adults said a college education is very important, compared to 75% in 2010. This is what a marketer would call a brand problem. The University of North Carolina is unveiling a refreshed brand identity and reorganizing its marketing structure to meet these 21st-century challenges. The centuries-old university has a storied history as a top-ranked academic institution and a legendary sports brand (thank you Michael Jordan). Chancellor Lee Roberts says that awareness isnt UNC’s problem. Everyone in North Carolina knows the school, and applications continue to climb each year. The truth is, it is a competitive landscape across higher ed. We are in a competition for research dollars, for rankings, and for the best students, Roberts says. We thought it was time to do a better job telling our story in a more proactive and effective way. In the contemporary media environment, you can’t just sit back and hope that everyone will recognize what makes you great and unique. You need to be a little bit more aggressive about communicating your story to the world. [Image: courtesy UNC] First. And for all. Its an obvious observation, but universities are not the same as corporations. The stakeholders involved in a brand refresh are many more than you’d find in a typical boardroom. Its why marketing at UNC has long been decentralized, spread across its more than 25 schools and units, all telling their own stories in a variety of ways. As a result, even the UNC logo had been spread thin. All told, there were 666 variations of the UNC logo being used. In order to more effectively tell the universitys story, as Roberts wanted, the decision was made to break down these silos and create a centralized marketing department. Adrienne King was hired in February, coming from Indiana University, as UNCs associate vice chancellor for marketing to lead the effort. Roberts also brought in former Phoenix Suns CMO Dean Stoyer, a veteran of brands like Nike, Under Armour, and ESPN, as vice chancellor for communications. This is the first time we’ve ever had a centralized marketing team at the university, King says. But this isn’t a situation where we needed to come in and start all over. [Image: courtesy UNC] King and her team partnered with creative agency 2×4 to conduct market research, do a comparative analysis, and develop an updated brand positioning. The research included surveys, focus groups, and one-on-one discussions with alumni, faculty, staff, students, and North Carolina residents. For starters, they found that the schools interlocking NC logo dates back to the 1870s, and it has remained the symbol alumni and North Carolina residents most identify with. From a brand perspective, it is internationally recognized. But more importantly, back at home we feel like it represents the people in the state that we serve, King says. This is the university for the people. And you can’t create a new logo that would have better equity than that. The brand refresh utilizes one version of that logo, as well as a standardized version of the iconic “Carolina Blue color. For a tagline, the school looked back at its history as Americas first public university and landed on First. And For All. [Image: courtesy UNC] In terms of the declining opinion about higher ed, Roberts says people tell pollsters they think universities are expensive, elitist, and don’t do a good job preparing students for the workforce. Well, here at Carolina, our tuition’s been flat for 9 going on 10 years in nominal terms, meaning it’s gone down by about 20% in real terms, and 82% of our undergraduates are from right here in North Carolina, Roberts says. We were just No. 3 nationally in the Princeton Reviews ROI survey. So we don’t think any of those concerns really apply to us. But again, that comes back to telling our story as effectively as we can. Meanwhile, competitors are stepping up, and not just the traditional rivals. Roberts name-checks schools like the University of South Florida, which is now a leader in new patents. You have an entire crop of new entrants who are gunning for the traditional top tier of public higher ed in the United States, and it requires everyone to continue investing, continue raising the bar, he says. [Image: courtesy UNC] Demographic cliff vs. Reputation cliff Twenty years ago, King wrote her dissertation on the role of marketing and higher education. I remember at the time marketing was seen as very much a negative term, and when you thought of marketing and higher ed, it was strictly enrollment focused, she says. For years, the postsecondary education industry has been bracing for what it calls the demographic cliff, when high school graduation numbersand consequently potential enrollment numberswill decline significantly. A Western Interstate Commission for Higher Education report says high school graduates will peak this year at about 3.9 million, and then start falling until there are about 13% fewer graduates by 2041. Kings says that given all the other challenges and narratives around the perceived value of a college education, more people within the industry are recognizing that while they were focused on that demographic cliff, they missed the reputational cliff that it has fallen off of. Now the work to repair and rebuild that reputation includes acting like a world-class brand and telling the story of its value. “I think often we in the public higher-ed sector take for granted that we are uniquely positioned within our states to drive economic development to benefit the people of the state, King says. I like to think our greatest investors are the citizens of North Carolina, and we need them to know all the ways that we are positively impacting their lives. That’s a very different position than strictly focusing on enrollment. That really is about reputation, and that’s what the focus is now.
Category:
E-Commerce
Amid the mass layoffs in tech and retail in the past month, YouTubes CEO Neal Mohan sent out a recent internal memo that hes also looking to lay off employeeswho volunteer. Mohan details how YouTube is undergoing a major AI-focused reorganization and introduces a Voluntary Exit Program with a severance package to eligible YouTube employees. This voluntary exit deal has been couched as an opportunity for employees, but its really just a buyout. Companies have long used this strategy as a way to reduce headcount, usually to avert traditional layoffs. For employees approaching retirement, voluntary severance may be a great opportunity, a wonderful deus ex machina late-career plot twist. But many employees worry that saying no, thank you now may mean an involuntary layoff later on. So how do you decide if you should take a voluntary layoff? Here are four questions to consider. Whats happening in your industry? YouTube has offered its employees a buyout because of AI restructuring. Duke University created a voluntary severance program in April 2025 in response to federal funding cuts. UnitedHealthCare invited an undisclosed number of employees to take part in its Voluntary Resignation Separation Program in early 2025 in response to the financially tumultuous fallout of the murder of its CEO, Brian Thompson, and to a 2024 cyberattack that cost the company $3 billion. In all of these cases, the organizations are offering buyouts because of larger technological, political, and economic forces. The decisions are about more than just whats happening in the organization itselfwhich may indicate that more changes are coming as the industries adapt. But not all buyouts are prompted by larger industry forces. Thats why its important to understand the bigger trends. Then you can better predict whether voluntary layoffs are likely to be the end of your companys reduction in forceor just the beginning. Typically, voluntary buyout packages are more generous than the kinds of severance packages that come with involuntary layoffs. What are your employment prospects? The best-case scenario for a voluntary layoff is either stepping straight into retirement or having a new job already lined up. Then your severance package becomes an unexpected pot of gold in the path you were already walking. Unfortunately, most of us arent that lucky. So if you werent planning on leaving before the buyout was announced, what prospects would you have if you took the voluntary severance? One of the upsides of voluntary layoffs is the opt-in window. Typically, employers offer a window of several weeks to several months to opt-in to voluntary severance, giving you some time to put out feelers for other potential job prospects. This can let you see what the job market is like before you make your decision. Whats in the severance package? While the specific severance package will vary from one organization to another, voluntary layoff programs typically make the buyout a tempting carrot in order to avoid more painful involuntary layoffs later on. Often, these severance packages will give volunteers several weeks or months worth of base pay, depending on the number of years of service. (And depending on which state you live in, you may be eligible for unemployment benefits once the severance pay has run out.) For instance, when Duke University offered voluntary severance earlier this year, it gave volunteers a compensation package equal to one week of severance pay, multiplied by years of service, up to a maximum of 26 weeks. But cash may not be the only benefit in your severance package. Your employer may also offer to pay health insurance benefits for a few months, provide career counseling, or offer financial planning services to help with the transition. What do you want? Learning that your employer is offering voluntary layoffs is stressful, but it doesnt mean the company has all the cards. The organization wants somethinga reduction in forcewhich means you have leverage. Because you can help give that to them, if they give you what you want. So just like when you were hired, figure out what you want and decide what youre willing to compromise to get it. Dont assume the severance package your employer offers is a take-it-or-leave-it proposition. Start with the severance compensation package. Just because the severance pay offered by the voluntary layoff program is capped at a certain amount doesnt mean you cant ask for more. The company is willing to pay people to quit, so feel free to ask for more money to give them what they want. Similarly, you could ask to be vested in the companys retirement plan if youre not fully there yet or ask to stay on the organizations health insurance until the next calendar year. The worst they can say is no. Deciding what you want to make leaving feel good can make a voluntary layoff a winning proposition for you, rather than an employment catch-22. Lay off me! If youre facing a Voluntary Exit Program or other euphemistically named quit-or-well-start-laying-people-off process, there are four questions you can ask yourself to help determine whether or not you should opt in. First, think about whats going on in your industry as a whole. If there are larger technological, political, or economic forces that are causing structural changes in your organization or in your industry, then it may make sense to take thebuyout, since there may be bigger shakeups on the horizon. From there, think about your employment prospects. Since buyouts typically have a window of several weeks for you to decide whether or not to opt-in, you have some time to determine if you can quickly find another position. Then consider whats in the severance package your company is offering, including the full payment amount and any additional perks that are included. Whats offered and how much is it worth to you? Finally, think about what you want. What would the company have to offer you to make walking away worthwhileand ask for it. Because a voluntary layoff is a negotiation, and you should treat it like one.
Category:
E-Commerce
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