It’s an Information Age-old debate among computer scientists, engineers, and business professionals: When it comes to implementing software to make your business run smoother, should you build it from scratch or buy a SaaS solution?
There are so many software options within different fields and areas of business, that it can boggle the mind. But, the two most important questions you need to ask yourself are:
- How much am I willing to spend?
- How much time do I have?
Now, let’s be realistic. Most businesses don’t have huge amounts of time and money to spend on software that’s not a core part of their product or service. While building your own text analysis software from open source can be rewarding in the long-run, it will take a lot of time, money, and countless headaches to create a workable solution.
With a proven SaaS solution, like MonkeyLearn, you can easily weave customizable text analysis software into your processes in a matter of days, with minimal costs. In this article, we’ll explain why the benefits of buying far outweigh those of building.
1. Building Your Own Software Takes Time
Even straightforward software, with cut-and-paste code and fairly simple algorithms, can take weeks or months to build. Do you have data scientists ready to dive in? Are you prepared to hire an entire team of qualified data scientists, engineers, and coders?
With complex text analysis software, hiring a team can take months. And when building custom software, there’s never a guarantee on timing estimates. If your team runs into an unforeseen issue, they may have to start from the beginning all over again.
Building a text analysis software:
Building a text analysis platform from scratch requires:
- Researching the proper natural language processing (NLP) and machine learning algorithms and understanding how to implement them
- Curating and tagging data
- Training machine learning models and tweaking the hyperparameters of each
- Building an API to integrate new models into your existing systems
- Building a user-friendly interface that non-technical teams can use to adjust models when needed
- Deploying your models with proper infrastructure
Depending on the sophistication, speed, and accuracy of the software you need, this will take a minimum of a few months.
So, while waiting on this new software, your team continues to manually sort customer feedback and tag support tickets, unable to focus on their main jobs. But the tickets don’t stop coming in, of course, so their volume grows. Then you have to hire more staff.
Spending hours on repetitive tasks hits team morale and affects data results, as tedium fatigue sets in. And humans are subjective, so each employee will tag results depending on their own criteria, further skewing your results.
This all leads to slower overall processes, defective data, incorrect conclusions, and bad decision making. Resulting, finally, in bad customer experiences, higher costs, customer churn, and less revenue.
The Benefits of Buying MonkeyLearn:
- Implemented into systems and processes in just weeks
- You don’t need a team of data scientists and engineers
- Pre-trained text analysis models up and running in just a few minutes
- Train your own models in a couple of hours
- Tailor models to the terminology of your field or business
- There’s no customization loss vs. building your own
- Easy and intuitive UI; no instruction needed
- Implement APIs with just a few lines of code
2. Building A Solution Is Expensive
So, let’s say you need to hire a team of data scientists and engineers to build your bespoke text analysis software. Multiply the hourly rate of your data and engineering team by the time needed, and you’re looking at a six-figure investment, upfront.
While open-source software is free to use, you’ll still need the right infrastructure, like high capacity on-site servers with powerful processors, which are quite costly. And, as mentioned above, these projects frequently go over the initial timeline, so you could end up spending more and more before your software is even ready to be implemented.
Furthermore, if text analytics isn’t at the heart of your company’s value proposition, you’re better off focusing your time and money on your actual core product.
With MonkeyLearn, you just pay the monthly license: usually, only three figures, sometimes up to four, depending on the plan. You can scale as you grow, so you’re not stuck spending thousands upon tens of thousands upfront.
3. Building is expensive to maintain
Even after you’ve deployed your exclusively built software, you still need a dedicated team to maintain and periodically upgrade it. You will have created whole new complex systems that only your data scientists and engineers know how to work. So you may just have to keep them on staff, indefinitely. Or regularly hire freelance engineers to maintain your systems, when bugs need to be fixed or you decide to add or change features.
MonkeyLearn maintenance: $0
- Included in your regular license support, so you’ll never have to pay extra
- No on-site maintenance, as servers are in the cloud
Build vs Buy Decision
With MonkeyLearn’s vastly customizable and easy-to-use (and implement) SaaS text analysis platform, you’ll save time, money, and not have to worry about constant maintenance. The plans are affordable and easily scalable to the needs and speed of your business.
Strategically, it’s better for businesses to focus on their core products rather than build their own text analytics software. Ask yourself the following:
Would you build your own project management tool?
No, you would buy Asana, Basecamp, etc.
Would you build a support ticketing tool from scratch?
No, because Zendesk and Front work great and have everything you need.
Would you build a CRM?
It sounds preposterous, doesn’t it? No, you would buy Salesforce, Hubspot, or others.
What about an entire text analysis platform?
Of course not. There’s MonkeyLearn.
Request a demo from MonkeyLearn and start getting the most out of your data.
Or, reach us at firstname.lastname@example.org.
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