Over the last few years, the business of messaging has changed in one fundamental way: it’s gone to the cloud.
The old wholesale way of doing things has given way to CPaaS (Communications Platform as a Service). Today’s aggregators have turned messaging into software accessible by APIs, addressing the enterprises’ needs directly.
This switch has transformed the commercial opportunity for messaging service providers. It’s made business messaging more flexible and accessible. That’s opened up the market to millions of enterprises large and small.
But, for messaging service providers it has also made operations much more complicated. And yet this deluge is also an opportunity. Why? Because of the avalanche of data generated by the growing constellation of customers, routes and campaigns. While also for enterprises, tool support is more than useful to analyse message streams, provider performance & financials, or other activities related to their products or user base.
Buried in this data are the insights that make it possible for your employees to:
- Run the business more efficiently
- Spot and remedy problems
- Identify new revenue potential
- Understand market trends
- Map KPIs
- Present data in a customer self-service portal
So the big question is: how is it possible to find these nuggets?
Well, it’s tricky. And in this blog, we will try to untangle some of the specific data analysis challenges aggregators face in trying to navigate this new reality.
Gather, understand and visualise
So how do most companies do data analysis now? Simple answer: they use a business intelligence (BI) platform. A BI platform helps companies gather, understand and visualise their data. BI tools deliver extremely useful analysis, but they are obviously very selective about the information they present. Why? Well, it comes back to the aforementioned volume of data, and its frequently unstructured nature. According to one industry survey, the average company has more than 400 different data sources feeding into its BI and data analysis.
This data will often be siloed and incompatible. So the challenge is to move it into a central location – a data lake – where it all exists together, usually in an unstructured way. From here, it is combined into a more structured entity, which is usually described as a data warehouse.
A BI platform will let employees run queries against this data, and then display the results as historical reports, real-time dashboards and other visualisations.
Be more specific
Today’s SMS platforms do an excellent job of helping a business to run and understand its messaging operations. But they only go so far. SMS platforms offer reporting functions that are configured just for top-level insights. They do not address specific use cases that uniquely affect messaging specialists. For example…
- Giving your team members the ability to aggregate and compare performance data across different products: for example, voice and SMS. Or letting them merge data about the same client, which is spread across different platforms.
- Giving a leader a complete overview of the team and of traffic patterns. Then he or she can make forecasts etc.
- Tracking swap deals between voice and SMS clients. If you buy a specific SMS volume and sell voice to the same client or vendor, you somehow need to track it. This can be made much easier if the BI can generate a single aligned graph.
- Creating an alarm for an unplanned-for surge of traffic. In the event that your customers run a sudden burst of campaign activity, you should be able to set up an alarm based on the maximum number of transactions per minute. This way, you can track and respond to surges (for example, by adding a new route) so you can handle the throughput.
- Generating a notification when something is wrong such as DLR or connection drop – then generating a response to mitigate the problem.
This is where BI comes in.
Clearly, any aggregator would gain real business advantages from running a BI tool that delivers any of the above insights. So how can they configure such a tool to pull the relevant data from the SMS platform?
The answer lies with SQL (Structured Query Language). The computing language that programmers use to find, pull/select, store and delete data from the data warehouse. An SQL specialist will be able to create an instruction that will isolate and process the data you need. Then allow your BI tool to attach to it so you can easily view it in reports or dashboards.
If you are unsure how to take control of your data analysis and maximise the insights it can deliver, we can help. We are not programmers, but we have experience in helping many diverse clients to understand and manage their data. We can certainly advise on the basics of how to get started and what to look out for. Reach out to GTC!
Global Telco Consult (GTC) is a trusted independent business messaging consultancy with deep domain knowledge in application-to-person (A2P) services. GTC provides tailor-made messaging strategies to enterprises, messaging service providers, operators and voice carriers. We have expertise in multiple messaging channels such as RCS, Viber, WhatsApp, Telegram and SMS for the wholesale and retail industry.
GTC supports its customers from market strategy through service launch, running the operations and supporting sales and procurement. The company started in 2016 with a mission to guide operators and telcos to embrace new and exciting opportunities and make the most out of business messaging. For more information or industry insights, browse through our blog page or follow us on LinkedIn.
