Data is the name of the game for the most profitable companies, and it’s not for nothing. When structured, and managed properly, it can be a significant revenue driver through a wide range of growth-related applications. After all, the best growth marketing decisions are the ones that are based on data analysis, and as we stated in one of our previous posts, you need to have a solid data infrastructure in place in order to enable data as a lever for growth. And it can all be done more efficiently, and at scale, when utilizing a codeless predictive AI solution.
Once armed with predictive insights, you and your data team will be in a better position to extract maximum value from your internal data, to make more informed decisions that will directly improve performance and profitability in the long-term.
With the right data team and the right tools, you will be able to tap into the power and potential of your internal zero- and first-party data, to gain actionable insights that can help your company in a variety of ways. For instance, you can use it to improve your product/service and the customer experience. You can also use it to identify customer purchase triggers, and how to anticipate or prevent churn. If you ask me though, I’d say the most awesome use case is the ability to predict future performance based on historical data. Not that I’m biased or anything. 😉
Now here’s the thing. Forbes reports that 89 percent of companies have adopted a digital transformation strategy. And it’s estimated that companies spent $2T (not a typo!) on data transformation in 2019. But despite this, less than 20 percent have achieved data success. Why? Well, they missed out on some pretty big opportunities due to a few shortcomings, which usually has to do with the interference of legacy tech, or choosing tools that weren’t the best fit for the company. It is also important to update the culture and processes, because magic won’t happen by just dropping new growth tools on unsuspecting team members.
Then there’s also the data silos issue. I’m not even talking about departments that don’t get along. I’m talking about a general disarray in data collection that complicates things for growth teams. It can lead to discrepancies in the data that’s collected. The clicks that product sees may be completely different to the numbers that marketing is looking at, thereby making it impossible to determine which channels and activities will benefit from further investment, and which should not be repeated. Research shows that firms with a strong corporate data literacy culture or workforce can increase company value by up to five percent.
It’s worth noting that the consequences of mismanaged data go beyond the element of complications. Ineffective analytics using siloed data sources can be expensive and inefficient, delivering minimal ROI. Meanwhile—a fragmented or poorly organized data structure can lead to compliance challenges if security and access permissions are neglected. All big no-no’s that can lead to growth teams wasting money on campaigns channels that aren’t going to be profitable in the long-term, and not increasing spend to the areas that actually would be profitable.
Now here’s the best way to transform your internal data points into something more actionable: by embracing predictive marketing. Predictive marketing uses past data to predict marketing trends and scenarios. By leveraging the old data with predictive AI, you can create a more optimized marketing strategy and drive better decisions. A predictive platform would use data models, statistics, and machine learning to predict future events, so your team can gain a better understanding of things such as which cohorts demonstrate the highest LTV, which campaigns will prove to be most profitable over time, what sorts of advertising will lead to an increase in sales, or even better retention in the future, and much more.
Imagine knowing exactly what your team would need to do today, so you can make and exceed your desired results tomorrow. You can acquire users based on their future value, shortening the time for your CAC payback, while raking in exponentially greater profits. Of course, you would need to ask the right questions, in order to choose the most optimal solution for your team. And if you’re looking into solutions anyway, you might as well select one that is codeless. Cause if you ask any developer, they would tell you—such solutions are difficult (and super costly!) to both build and maintain in-house.
There are plenty of benefits to using a codeless predictive platform. The greatest perk of all might have to be the fact that you and your team will be spared the hassle of the most tedious elements of data analysis. Jokes aside though, there’s little-to-no maintenance involved, thereby freeing up time and resources. Feedback cycles are also quicker, and insanely accurate. By extension, it makes it possible to use the AI components to produce real, reliable predictions, using real, sophisticated techniques that are based on the best LTV-optimized data science approaches.
Granted, codeless predictive solutions do not exist to replace data scientists. As you can see in our blog, we ❤️ data scientists. Simply put, a codeless predictive platform can help data teams use AI to rapidly address (and solve) concerns that are tied to growth and profitability. All the heavy lifting will be done by the expertly developed and tested platform itself. Without a codeless predictive platform, a data scientist can create one-off strategies that are based on single data sets. With the backing of a predictive platform though—scalability can be achieved sooner across numerous verticals simultaneously, and with greater returns, all while eliminating the main challenges that are getting in the way of your company’s growth. And you can sit back with confidence and let the tech do its thing, because it has been tried, tested, and refined thousands of times before entering your radar.
Now is the time for you and your team to turn to tech, so you can optimize your growth strategy by placing actionable predictive insights front and center, to serve as a guiding light to profitability. And it can all be done without compromising on quality, thanks to LTV optimized actionable insights.