It’s a good news/bad news scenario for communications service providers (CSPs) in today’s digital world. The good news? The industry is in a tremendous position to capitalize on the explosion of data-driven digital transformation.
Smartphones, connected devices, Wi-Fi and the networks themselves will continue to put a wealth of data directly into the CSP's hands. The confluence of internet, mobile, TV and streaming truly position organizations to make good on the promise of delivering all communications to the household, business and beyond.
Now, CSPs are beginning to shift their focus from network performance to customer experience. A recent study by TM Forum found that 80 percent of operators said they consider enabling customers to engage in a consistent and seamless experience across multiple channels a high priority. And 73 percent suggested that developing stronger customer relationships also ranks among the most important digital drivers.
The bad news? For many organizations action has not caught up to intent. The latest Net Promoter® Score (NPS) benchmark report conducted by Tempkin illustrates just how far behind other industries CSPs lag. TV and internet service providers hit rock bottom with a dismal average score of 3, a low of -9 and a high of only 17. Wireless carriers fared only slightly better at average 25, low 9 and high 37 respectively. For comparison purposes, USAA hit the top spot with a score of 66 and most industries saw their highest-scoring customer experience leaders in the 40s and 50s.
Free research paper
Read this SAS-sponsored research by TM Forum to better understand the important role customer journey analytics and machine learning can play in improving customer journeys.
Meeting expectations along the customer's journey . . . or not
Just because the industry lags in customer satisfaction doesn’t mean customer expectations are lower for CSPs. Savvy consumers expect a digitally enhanced customer experience that crosses traditional and digital channels. This means timely, relevant communications that conform to personal preferences and highlight real customer knowledge. Unfortunately, it is not that easy. Meeting expectations at every stage of the customer journey requires that CSPs understand how customers navigate all channels. But customer journeys have become non-linear. Modern interactions have customers bouncing from channel to channel, and converging business models for many CSPs means those journeys also cross business silos.
Consider longtime wireless customer Linda who had a four-year-old handset and a grandfathered “customer loyalty” service plan. She also purchased internet and landline services from a different business unit within the CSP. For several years, the wireless group periodically sent her text messages highlighting her eligibility for a phone upgrade. When Linda started experiencing problems with her mobile phone (lack of storage and short battery life), she decided to take them up on their offer.
Using the store locator app to find the closest store, she arrived to find a digital check-in kiosk and a 30-minute wait for an associate. Upon payment, she discovered that with her new phone came a new plan (the “loyalty plan” was discontinued) and that “upgrade eligible” now meant paying full retail price for the phone in exchange for no long-term contract.
Her last shock came with the first bill. A bill that looked significantly different and contained a one-time upgrade fee – charged in addition to the full retail price of the mobile phone. Eventually, a call to customer service explained the difference in bills but no elimination of the fee. Unbeknownst to the wireless group, Linda had also been experiencing ongoing internet and landline problems due to an aging infrastructure. The result of Linda’s unsatisfactory experience? When a competitor offered a bundle with internet, landline and TV, Linda switched all services including wireless to them.
Quit looking behind you – you are not headed that way. Anonymous
Customer journey analytics add the 'journey' to analytics
In the TM Forum survey, lots of service providers are trying to analyze and map customer journeys, but:
- Fewer than 20 percent maintain accurate customer profiles.
- Less than 10 percent deliver personalized content.
- Fewer than 10 percent are implementing analytics and machine learning to help.
Most are vulnerable to situations like the one our provider faced with Linda. While changing pricing and plan options are inevitable, applying customer journey analytics and real-time information to Linda’s journey could have turned a bad experience into a good one.
The communications in this example were not personalized, the channels were not coordinated, and some of the pain points could have been anticipated via customer journey analytics. For example, one type of customer journey analytics focuses on performance of networks and handsets. For this analysis, current data from the network on dropped calls and inconsistent Wi-Fi connections, as well as data from Linda’s phone on free memory capacity and battery status could be compared to historical data for similar phone models. This would have highlighted for the marketing team the exact timeframe that Linda’s phone had reached the end of its usefulness mobile in terms of battery and memory.
Customer segmentation analytics might have positioned Linda into a segment of high/long handsets – a group that purchases high-end newest model phones when they purchase but that also keeps their phones until they break. Rather than continuing to send periodic generic upgrade notices which might be appropriate for customers who frequently trade up to the newest model, the CSP could have sent a single, personalized and timely upgrade message triggered by Linda’s cell phone issues and the customer journey analytics results.
Customer journey analytics using journey mapping and frequency/type of customer service calls and complaints (correlated to actions such as phone upgrades and plan and pricing changes) could have highlighted a common pain point – customers encountering forced plan switches and billing practice changes. Customer journey analytics would have revealed that Linda was close to experiencing this pain point. The personalized message to Linda triggered from her on-going phone issues could have not only acknowledged her need for a phone upgrade but also provided information about recent pricing and plan changes, and provided a click-thru link to a service rep (with a prompt to that rep about the potential issues).
Real-time event streaming could have facilitated that her store location search results be augmented with current wait times for locations close to her while also prompting the store sales rep to review with Linda what her new bill would look like compared to the old.
And, if the CSP had been able to develop and use a true 360-degree view of Linda using customer journey analytics, the store sales rep would have understood that she was a valuable multi-product customer (land-line and internet as well as cell) and the upgrade fee could have been automatically waived based on her customer loyalty across all the business lines.
Customer experience is expected to be the next key battleground for most industries, telecommunications included. The low NPS scores and lack of real application of customer journey analytics to shape customer journeys means there is a wide-open playing field with tremendous opportunities for businesses that focus on customer needs.
- Article Five trends that will reshape customer experienceApplying the latest research from HBR gives a new twist on this surprisingly relevant 2015 list of CX do’s and don’ts.
- Series The value of marketing metrics at VisaMarketing metrics are the bane of many marketing teams, but at Visa metrics not only matter but make a real difference in strategy and brand value.
- Article Customer journeys: How to be ready when customers visitAnalytics makes customer journeys better. By gathering insights from detailed and diverse data sources, you'll have the right offer at just the right time.
- Article Moving beyond the ad serverAd servers take a broad-brush approach to delivering advertising. But there is a better way. One that allows you to finesse your offerings to paint the best picture for visitors by using data analysis to gain profitable insights.