Business
5 Reasons Why Any Successful Shopify Dropshipping Business Needs The Right CRM

Here at SaleSource we often get questions like: “Is dropshipping legal?”, “Is dropshipping dead?”, etc. It’s important to get it out of the way first – the short answer is no, dropshipping is not dead and yes, dropshipping is absolutely legal.
Next off, what is a CRM? Well, CRM stands for customer relationship management. Essentially what that means is your CRM is your customer database and your leads database, and also your business management software. So it’s really important. If you want to effectively manage your business and scale your business, you’re going to need a great tool to do so and that’s a CRM. And that’s why it’s so important to have the right CRM. So if you’re not using a CRM, if you’re using yellow pads or spreadsheets, it’s a no-brainer, you need a CRM. And if you’re using a CRM that you don’t love, maybe this article will help you identify the right CRM to use to truly grow your business.
So there’s really six points that I want to touch on to help you determine if you’re using the right CRM for your business or which CRM you might use that would be the right CRM for your small business, so let’s go through those one by one.
1. Lead management
So the first thing to look for within a CRM is the appropriate lead management tools you have for your sales team. For any small business, such as shopify stores, to grow – they really need a good convertible process with regards to taking a lead and turning it into an account, that’s your sales process. And all of the leads that you have are your lead pipeline. And so you need a sales team to be most effective to grow your business in terms of taking those leads and turning them into accounts. Well, your CRM really helps for that because CRM will allow you to do things like when somebody fills out the lead form on your website or on social media, let’s say, like on an ad, it will automatically build that contact within your CRM, automatically assign it to your sales rep, and also give them the process that they should follow in order to close that deal. Whether it’s an initial call and then seven days later an email follow-up, and then another call; you can predetermine what that needs to be and you can build that template right into your CRM so that your sales team can just follow that and close more deals. So a CRM is really, really valuable because it allows you to optimize that process so that all of your sales people are following the same process with the same piece of software system so that you can have consistent performance over time.
2. Account management or customer management
Customer management is really important because you don’t want to have a bad customer experience and you want those customers to keep coming back. So a CRM allows you to do that because it does such things as when a lead becomes a customer, it unlocks additional fields of information that can be populated by your account managers and your customer service reps, et cetera, so that you have all the information you need for all of your customers. It can also do things like send email communications automatically. So as that customer moves through their life cycle, at key points when they need certain information sent to them, instead of counting on somebody to do this manually all the time, your CRM can serve as an automated worker for you, basically, and send this messaging out in an automated way to your customer base, which is really, really powerful if you create these journeys in the right way. The CRM also has all the notes and history logs that you might have had on a client, and it pulls in all of the data and all the pieces so that you can see the full story of each customer within a CRM. So if you don’t have that right now, definitely take a look out there and see if there’s a CRM software that fits what you’re looking for with regards to customer management.
3. Task management tools
So task management, really important. Basically everybody in your company has tasks that they’re trying to accomplish every single day. And so a CRM is a great way to have that basically streamlined in a more automated way to where as certain tasks are completed, other tasks are unlocked. So it really helps you to identify the things that need to get done. I found over the years that if somebody doesn’t really have their day planned out, they’re not very efficient because they’re always spending a lot of time thinking about what to do next, instead of just having tasks organized for them so they can come in and just start knocking them out one after the next. So a CRM allows you to think proactively because you can create these tasks for different leads you’re talking to, for different customers you’re working with, you can schedule them out so that you’re always building out your future plans of what needs to get done proactively so that when that day comes into today, I have the things that I need to do right in front of me and it keeps a log of all of this for me automatically within the CRM so that I always have a history of what’s been done.
4. Project management tools
The fourth thing to look for within a CRM is the appropriate project management tools that you might need. So you always have these little side projects going on, right? Whether it’s something you’re personally doing, or something for a customer, it could be a project you’re doing for a customer, it could just be something you’re doing yourself because you just want to do some self-development or something like that. Within a CRM, you should be able to create a project with different stages within it and tasks that need to be accomplished within each of those stages. And then you can use those templates moving forward if you wanted to, maybe it’s a project that you typically do for customers over and over again, right. Maybe it’s like a kitchen remodel, you need to do these things whenever there’s a kitchen remodel, it’s like a checklist, it’s a no-brainer. So if that’s a service that you provide, every time you have a new customer that needs a kitchen remodel, you just add that project to it and then your team can start working on it. This is really effective because it allows you to streamline and make sure that you have all of the checklists or processes built out ahead of time for all of your projects. And then if you ever need to add a stage or add a step, when you do that, it immediately is added to all the other projects because it’s a template. And so it really helps your whole team make sure that nothing gets missed along the way.
5. Company calendar
Company calendars are really nice because it helps you just see what’s going on at the company level with regards to all the events, things coming up, different customers that you’re interacting with for the day, that kind of a thing. So we all have our personal calendar usually in our email whether it’s in Gmail or those things, and that’s really good. What I’m talking about here though is a company calendar. As a team, you want to be able to see what the rest of the team is doing, and so a CRM is nice because the calendar there shows you from a business perspective what’s going on for the day for not just you but you can toggle and you can say, hey, show me everything that, all the events happening today for my whole team. And that helps you identify what’s going on as an organization, especially if you’re a manager, so you can make sure that you’re effectively managing your team appropriately.
Business
MetaWorx: Building Full-Stack AI Teams, Not Just Automation

Automation still dominates most headlines, yet the returns often fail to meet expectations. A sprawling chatbot rollout might shave a few support tickets, but it rarely shifts the profit-and-loss statement in a lasting way.
McKinsey’s 2025 workplace survey pegs AI’s long-term productivity upside at $4.4 trillion, but only one percent of enterprises say they’ve reached true “AI maturity.” MetaWorx, a Dallas, Texas-based AI employee agency founded by Rachel Kite, argues that the shortfall has nothing to do with models and everything to do with people.
“Treat AI like a point solution and you’ll get point-solution results,” shares Kite. “You need a roster that can carry the ball from raw data to governance, or the whole thing stalls at the proof-of-concept phase.”
The pod blueprint
When a plug-and-play automation script collapsed under real-world data drift, costing Kite a lucrative contract, she sketched the six-person “pod” that now anchors every MetaWorx engagement:
- An infrastructure architect to tame compute costs.
- A data engineer to secure and shape pipelines.
- An applied scientist to prototype models against live feedback loops.
- An MLOps engineer to automate rollback and retraining.
- A domain product lead translates forecasts into features users actually notice.
- Ethics and compliance analysts to stress test outputs for bias and keep the audit.
The team’s first sprint still delivers a quick-win bot — “small enough to calm the CFO,” jokes Kite — but the roadmap quickly pivots to reliability, explainability, and eventually optimization. By tying every algorithmic decision to a quantifiable business metric, the pods turn AI from a science project into a growth lever.
Recruiting for curiosity, not credentials
With Bain & Company predicting a global AI-skills crunch through 2027, MetaWorx has stopped chasing unicorn résumés. Instead, it hires “adjacent athletes”: a computer-vision PhD who hops from medical imaging to warehouse surveillance, or a former journalist who recasts her nose for story into prompt-engineering finesse.
“Domain expertise expires fast,” Kite says. “What doesn’t expire is the instinct to ask better questions.” The result is a lattice of overlapping skills that stays flexible when models wander into the long tail of edge-case data.
A culture of rapid experiments
Inside MetaWorx, every idea faces the same litmus test: ship something — anything — into a user’s hands within 21 days. The “three-week rule” forces prototypes into the wild early, where failure is cheap and feedback is swift. Post-mortems, including cost overruns, are circulated company-wide, erasing any stigma associated with missteps.
That laboratory mindset powers velocity. “Our first model is almost always wrong,” Kite admits, “but version 1.0 is the tuition we pay for version 2.0.” The philosophy echoes her TEDx talk on resilience: progress is iterative, not heroic.
How leaders can steal the playbook
Executives itching to replicate MetaWorx’s results don’t need a blank check. Kite offers a five-step sequence:
- Inventory pain points, not tools: Walk the P&L line by line and tag the friction you can measure.
- Map the stack to the problem: A recommendation engine, for instance, requires behavior data, retraining triggers, and feedback capture — automation alone won’t suffice.
- Stand up a pod: Reassign existing talent into a cross-functional tiger team before hiring externally; the chemistry test is free.
- Measure the story, not just the statistic: Pair model accuracy with human-scale metrics like ticket backlog or employee churn.
- Budget for the boring: Reserve at least 30 percent of spend for MLOps and governance; Stanford’s HAI review links most AI failures to neglected upkeep.
Taken together, those steps shift AI from a pilot novelty to an operational habit that compounds value rather than topping out after an initial PR splash.
Character still scales faster than code
MetaWorx plans to double its headcount this year, yet Kite insists the secret isn’t a proprietary framework or a monster war chest. It’s credibility. Clients see a founder who has wrestled with the same outages and surprise bills they face. That authenticity converts skeptics faster than any algorithmic novelty.
“Tools level out,” Kite says. “Culture compounds.”
The insight lands in a marketplace still dazzled by generative fireworks. Yes, MetaWorx ships models and dashboards, but its true product is a mindset: resilience over rigidity, questions over credentials, experiments over edicts. In Kite’s world, automation is merely the appetizer. The main course is a full-stack team that knows why the model matters to the business and who owns its success after launch day.
And that, Kite argues, is how AI finally graduates from cost-cutter to growth engine, one curious pod at a time.
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