Nowadays, the best way to make informed decisions about your business is through data analytics. Relying on the manager’s hunch doesn’t really work anymore. And this is where SQL analytics can help you take your business to a whole new level. Structured Query Language (SQL), is an immensely helpful tool that allows you to access, process, and analyze data stored in databases in your organization.
This technology comes in handy, especially concerning marketing and sales purposes; you can use it to optimize your marketing campaigns, understand customer behavior and needs, and, in some cases, even predict future sales trends.
Read on to see how it can be done with SQL analytics.
Why should you use SQL for marketing and sales analytics?
As we’ve already mentioned, SQL analytics are incredibly useful for marketing-slash-sales purposes, and there are at least four good reasons for that:
- Ability to handle even large datasets: With SQL analytics, you can easily process and analyze data comprising even thousands of records. Imagine you want to analyze all the orders placed in your business in the last five years – that’s what you can do with SQL analytics with ease!
- Many customization options: SQL is a very versatile tool that can be adjusted to your business needs and preferences. You can even set it to answer specific questions you want to ask about your database.
- Data analytics from multiple sources: Thanks to SQL analytics, you can analyze data coming from different sources (e.g., your website, your online store, your CRM, etc.) so that you can get the full picture of sales and marketing in your business.
- Improved decision-making processes: SQL analytics provides you with all the input you need (frequently in the form of actionable insights) to make informed decisions about your business.
Now, let’s have a look at some of the use cases you can implement in your business.
5 use cases to use SQL for marketing analytics
- Customer segmentation: Segmenting your customers is essential to running effective marketing campaigns. Thanks to SQL analytics, you can identify different groups of customers within your databases. You can do so based on their demographic characteristics, purchasing habits, annual spending, engagement in brand communications, etc. As a result, you can easily create different audiences and craft your marketing messaging so that it resonates with different recipients.
- KPIs: Are you always 100% certain you know which campaigns have been effective in your business? You can ask SQL analytics to calculate KPIs (key performance indicators) for different marketing and sales campaigns in your business. This feature is especially helpful when it comes to calculating ROAS (return on ad spend).
- CLV: Customer lifetime value is another metric that many businesses struggle with. Use SQL marketing analytics to calculate customer lifetime value. It will help you plan future campaigns as well as marketing and sales-related investments.
- Audience analytics: If you pursue the omnichannel strategy, you likely have many different traffic sources in your business. With SQL analytics, you can put all those sources together and analyze your traffic in one well-organized space.
- Customer churn analytics: SQL analytics can help you identify customers who are likely to leave your company, stop placing orders, and/or interacting with your brand. You can use this input to focus on those customers and try to retain them for a longer period.
5 use cases to use SQL for sales analytics
- Sales funnel analytics: Use SQL analytics to analyze your entire sales funnel/pipeline to identify improvement opportunities. For example, SQL can help you spot bottlenecks where the sales process is frequently stopped or dropped altogether.
- Lead scoring: SQL analytics will help you analyze all the potential sales opportunities in your business and help you focus on the most promising leads (e.g., based on their readiness to buy from you). Naturally, this will support your sales efforts and help you close more deals.
- Sales forecasting: Thirdly, you can use SQL sales analytics to analyze historical sales data in your business. With this input, you can spot patterns that have been affecting your sales in the past. At the same time, you can also predict future sales levels and prepare for worse months.
- Cross-selling and upselling: These two sales techniques can be very helpful when it comes to increasing AOV (average order value), but spotting all the cross-selling and upselling opportunities is not always easy. SQL analytics will help you identify hidden cross and upselling opportunities.
- Sales reps’ performance: Lastly, you can use SQL analytics to analyze your sales reps’ performance and spot areas for improvement. For instance, you can see what they need additional support with and create training/coaching programs for them.
Conclusion: How to identify your needs to use AI to drive ROI
Artificial intelligence can give a solid boost to your SQL analytics. In order to assess whether you actually need AI, focus on these three questions:
- How complex is your data? If you deal with dozens of data sources and hundreds of different data points, AI can surely make data analytics quicker and easier.
- Does your SQL analytics solution require a lot of manual work? Even though SQL analytics is a tremendous tool, it still requires some manual work. If you want to save time and access all the necessary information right there on the spot, the only way to achieve that is with AI.
- Do you need predictive analytics? While “standard” SQL analytics can offer some insights about future sales levels, if you want to know more about your company’s future performance, you should employ AI to do so.
If you’d like to know more, take a look at our LLM-Powered Data Analytics.
