How to Improve Call Tracking and Marketing Analytics With AI

AI empowers marketers with data and top-of-the-line analytical capabilities. With this, they’re able to improve call tracking. The question is, how is this done and how can you ensure that you’re making the most of this technology? Read on to find out.

Incoming: Customer Calls - Why You Need to Pick Up the Phone

Calling customers remains an important form of communication with audiences. It provides a direct line and gives your business a literal voice. Many people prefer this method as it can offer quick turnarounds on solutions. It is useful at various stages of the consumer journey, whether it's research-related queries, support services when making a purchase, or the scheduling of appointments. In other words, it offers value to the customer for businesses across a variety of industries.

So, where does call tracking fit into all of this?

With better tracking in place, you’re able to be precise in analyzing your performance and gain greater insights. This can help you to improve your services going forward by identifying gaps and opportunities. This has a positive effect for all involved - the call center will be able to optimize their work, and your customers will enjoy increased satisfaction which then leads to loyalty.

Call Tracking Improves Marketing Analytics

Call tracking reports are packed with analytical data. When you have AI to record, store, and organize this information, you’re able to make better sense of what you’re looking at. It helps you in identifying patterns and improve your predictions going forward.

Depending on what you’re calling customers for, you’ll be able to analyze the channel itself and your call campaigns. If you think about analytics in its most basic sense, you could easily use phone records to determine the volume of calls, the locations, and the lengths of these conversations.

That’s where AI comes in. It tells you so much more.

How to Use AI to its Fullest Potential

With AI, you can get an understanding of the qualitative elements of your calls. This is imperative as it sheds light on the quality of the calls received. Instead of just knowing how many calls were placed and received, you can find out how many of those calls were from quality leads and how many leads to conversions, for example.

There are various AI technology solutions on the market for businesses to use. These transform the raw information collected into definable analyses at scale. The reports generated can be customized to suit your KPIs and to measure your performance acutely and accurately. These AI-driven analytics essentially form part of your lead generation strategy.

If you’re using a CRM system like HubSpot, you’ll be able to keep track of all of your communication with each customer. This allows you to develop deeper relationships, with AI technology being used to draw comprehensive insights.

When you have AI available, use it to dig deeper. Find out who is calling you - have they called you before? What do they need right now, and what can you offer them in the future? These insights are available at a moment's notice to illustrate important information in real-time. You can also track the calls to observe the quality. The key is having good conversations that lead to desired results.

Many businesses implement telesales to connect their digital presence with traditional marketing. To learn more about how you can do this, read Digital Marketing + Telesales = Success

Now, let’s return to the question at hand: How can you improve call tracking and marketing analytics with AI?

To answer the first question about how to improve call tracking with AI, you, first of all, need the technology solution to do so. If you’re outsourcing a call center, be sure to check which analytical tools they use. Equally as important to have this technology available to you is the ability to use it. You need to be able to draw the relevant insights so that these figures drive growth and necessary change.

That brings us to the second part of the question: how to improve marketing analytics using AI. We’ve covered analytics above, but the marketer needs to include these figures in their overall marketing strategies. It is also important for them to let these analytics inform their marketing strategy at its core since valuable information can be learned about your customers that apply to the bigger picture.

Think about it: many marketers have an idealized impression of who their customers are, but don’t take the time to speak with them directly and learn from them and their changing needs regularly. Call tracking makes that possible.

See, AI saves marketers time. To gain insights, they no longer have to listen back to call recordings. This technology can find data and detect patterns that marketers can use to their advantage. In some cases, it may be possible for language detections to transcribe text and identify keywords.

Here are some practical tips for handling call tracking analytics:

Link the metrics back to ROI so you can better understand your sources, leads, and conversions
Have strategies in place that enable you to learn more about your targeted audiences including their driving forces, behaviors, and preferences
Have caller workflows ready to go so that you can offer your customers quick and positive solutions
Have knowledgeable, attentive, and friendly agents dealing with customer calls
Consider an inbound calling strategy or campaign
Set out your goals and KPIs so that you can accurately measure optimize your performance
Marketing teams need to be working with the agents - a transparent and mutual working relationship is most beneficial
Utilize the ability for AI to make predictions based on historical patterns and to incorporate various sets of information, including relevant first-party data

If you’re communicating with your customers over the phone, you’ve got to tap into the many benefits that AI can provide you with. With these analytics available on the market, your marketing team will be able to improve your business’s performance in several ways by using critical and valuable information that is technologically designed to identify, adapt, and improve.