Think not what AI can do for Telcos, but what Telcos can do for AI
It seems unlikely that telcos are a rich breeding ground for the next set of breakthroughs in AI, but they are, they just don’t know it.
Personalization is a must-have for any telco in today’s hyper-competitive environment. Being able to stand out from the noise and deliver relevant, timely messages to the right customers is essential in securing a return on investment and keeping satisfaction high.
However, to benefit in the long run, it’s vital to know exactly which elements of this strategy are working, and where improvements can be made. Getting true personalization right at an individual level remains very difficult, which makes it especially important for telcos to see where their measures are succeeding.
Unless you can effectively analyze campaigns and apply the learnings from this to future efforts, your personalization will never reach its full potential. To do this, it’s important to know what areas to focus on.
The high-level goal of any personalization strategy will be to increase conversions. But to be effective in the long term, the analytics process needs to start before the first communications have even been written, to identify and define key objectives for each campaign.
Generally, these tend to fall into two categories. Firstly, there are specific campaign goals, such as adding a line or upgrading a device. These types of conversions are usually easy to measure. But then there are those that are less directly tied to a specific conversion, and these need especially close attention.
Such aims may include retention, usage of loyalty schemes and signups for partner programs, which can be trickier to analyze. For instance, in some cases, telcos themselves may not have direct visibility into how many of their users are joining partners, making it especially difficult to measure the results of such loyalty campaigns.
To overcome these challenges, it’s vital to identify right at the start of a campaign exactly what success will look like and what metrics will be used to measure this. Knowing precisely who your target audience will be for a campaign is an important first step. Then, setting up clear benchmarks for factors like engagement rates ensures everyone involved with the project knows what constitutes success.
Another critical element of setting these goals is establishing who your intended audience is and understanding who they are as individual people, not just targets for a campaign. Matching the right customers to the right campaigns is vital to success, as it ensures you know what your expected outcomes are and that the offers are being targeted at the people most likely to respond.
For example, a simple analysis may suggest a customer is eligible for several offers, such as a device upgrade or adding a new line. But if different, siloed teams are each managing campaigns with these targets, they may receive multiple offers – which may be irrelevant or even contradictory – and conclude the telco doesn’t know who they are, making a conversion less likely.
If offers can be combined in the right way, to address the specific interests of a customer in an appealing way, they may be able to enjoy better results. For instance, a customer on a very low-tier plan with an older generation phone may not often be considered a likely target for a service plan upgrade, as the data may suggest they have limited usage needs and any upsell attempt will simply be offering perks they don’t necessarily need.
But if they also qualify for a phone upgrade, these offers could be combined to upgrade their plan and get a free upgraded phone at the same time. This can make an offer seem much more attractive and persuade a skeptical customer they’ll get value from an increased price. This is how personalization isn’t just about optimizing a message, but about targeting the right people in the right way.
Being able to compare the impact of a personalization campaign to more generic efforts is a key tool in visualizing the effectiveness of your messaging. However, it can be easy to fall into the trap of attempting to cover too much ground at once, which can make it impossible to glean any useful information from such analysis.
Therefore, it’s vital that telcos conduct A/B testing – and make sure this is done in as controlled and limited a way as possible. As soon as you start adding variables C, D and more of the alphabet to the mix, the benefits are lost, as you won’t be able to tell which personalization elements are making the difference.
A big part of this is knowing what to test against. Comparing creative imagery, for instance, can quickly become challenging, as this can be highly subjective – and the goal of any testing should be to eliminate these variables. If you’re testing two different lifestyle images within a message, it can be hard to tell exactly why customers may prefer one over the other, which means results will be difficult to extend across a large scale.
Therefore, keeping testing as controlled and objective as possible is vital. All this may take more time, but it’s vital that companies have the patience to see this through. With the right, careful approach based around the clear initial goals and objectives you should have set out at the start, you can draw vital learnings about customers and what they truly want.
By testing personalized campaigns against generic alternatives through multiple A/B efforts, it should start to become clear which elements are most effective. But you still need to understand how this translates to wider campaign performance and how it lets you refine audiences for future campaigns.
You need to make sure you’re looking at the right KPIs for each step of the campaign in order to define success. For example, if you’re running an A/B test on an email where the measure being tested is the subject line, is the conversion rate really the best metric of success? For this particular effort, open and engagement rates should be the most relevant metrics.
This is why it’s so important to set clear objectives early. Making them as specific as possible ensures you don’t get overly focused on more wide-ranging metrics that may be affected by multiple factors. Setting out a clear plan and sticking to it will provide much more useful insight for the future.
It’s also vital to remember that personalization should be part of a long-term effort. It’s often not realistic to draw conclusions from a single campaign and overlay them onto an entire strategy. Sometimes, you can learn just as much from a failed effort as a successful one, as long as you ask the right questions and draw the right conclusions.
Human instinct is often to look at one campaign and draw life-long conclusions from the results – for good or bad. But by taking a step back and ensuring you’re treating each campaign on its own merits, with its own goals and metrics, you can build up a much better long-term picture of how to apply true personalization in the most effective way.
Image credit: iStockphoto/GaudiLab