One channel largely neglected in social media marketing conversations is the growing importance of podcasts. While not as sexy as SnapChat or Secret, this relatively old channel is becoming a critical component of effective social media marketing. Podcasts were originally built for the iPod (hence the name) but are now listened to not only via iTunes but also multiple IOS and Android apps and even via the good old Internet.
Why podcasts now?
Looking at the numbers, the growth of consumer interests in podcasts is clear. A Washington Post story reported that podcast subscriptions on iTunes reached 1 billion. An Edison Research report shows that over 39 million people listen to a podcast last monthly and that 20 percent of podcast users consumer six or more podcasts weekly.
The accessibility of podcasts has led to their growth. As the Washington Post writes, “despite some early enthusiasm, podcasts faded in popularity in the early 2000s, partly because of the many steps required to download them and play them in a vehicle. The introduction of the iPhone in 2007 changed that, making podcasts as convenient to access as a Netflix show. It’s easier to play them in cars, too, as automakers build wireless media functions into more and more models. And faster WiFi and mobile data speeds have made podcasts a snap to stream.”
Podcasting increase retention
There are multiple benefits for integrating podcasting into your social media marketing mix. First, they increase engagement. Rather than a few seconds to share a message with your customer or player, you have minutes or more to share your narrative. Rather than a superficial message, you can go in-depth on the value your product has to the user, how to get the most out of your product, the background of how it was made, etc. These messages can have a strong impact on users, if they get more value out of the features they are more likely to keep using it. Continue reading “The power of the podcast”
Two personal, and comparable, experiences recently showed directly how customer service impacts lifetime value. As many of you know, I travel frequently on business and rent a car about 40 weeks per year, making me a “whale” to car rental companies. I am also relatively loyal to companies, I limit my choices to two companies and probably use my favorite 75 percent of the time.
The Ace Rent-A-Car story
A few months ago, I rented a car from ACE Rent-A-Car. I had rented from Ace about 15 times already in 2014, for 30+ weeks, from its Chicago location.
After going out for dinner one night, I discovered that my rental car had a flat tire. Unfortunately, the car I rented did not have a spare tire (yes, there are cars now that are sold without a spare). It was about midnight in Chicago and it was cold so I called Ace with my problem even though I had waived roadside assistance. The first two times I called I was placed on hold 5-10 minutes and the person had no idea how to help. The third time I called they were friendly but explained they could not help because they were acquired by Budget Rent-A-Car (still not sure if it was a system-wide acquisition or the O’Hare location) and gave me a phone number for Budget. I was annoyed as it was getting quite late and I did not feel it was appropriate to rent cars that did not have a spare (and not let the customer know). Continue reading “How CS can impact LTV”
I came across a great post by VC Tomasz Tunguz on a great growth mechanism: negative churn. In effect, negative churn creates the same compounding effect as a high-rate bond; over time it generates tremendous growth. Negative churn means that the actual churn rate, the number of customers or players moving out of a collective group over a specific period of time, is lower than the increase in the value of the retained customers.
What is negative churn
Tunguz uses a great example to illustrate negative churn. Say your company has a five percent monthly churn rate, which means that five percent of your users quit each month. In Tunguz’s example, the remaining 95 percent of the customers increase their spend with your company by ten percent, so total revenue from this cohort (group) of users is equal to 105 percent of the revenue from the previous month. Even with 5 percent monthly churn, each month this cohort of users becomes increasingly valuable.
In the 5 percent monthly churn case, the company exits the year with $919 in monthly recurring revenue and the customer lifetime value (assuming a one-year lifetime and no virality) is $77. In the negative churn case (where you have a 10 percent monthly increase in spend), your company’s revenue is 73 percent larger at $1592 and the LTV is worth $133.
In both cases, the company has the same number of customers (or game, players). But with negative churn, revenue is over 70 percent higher. This shows the power of compounding growth every month.
This graphic from Tunguz’s blog illustrates the opportunity:
How to achieve negative churn
Continue reading “How negative churn can be a strong growth driver”
One theme that comes up repeatedly in what I read, and thus write, is the importance of Triggers. In my February analysis of Jonah Berger’s book Contagious, I discussed how triggers are one of the five core elements to creating a product with word of mouth. Then in June, I discussed Nir Eyal’s bestseller, Hooked, in which the author builds a model on creating a habit-forming product; triggers represent one of four phases of the model. Given the importance of word of mouth (virality) and habit (retention) as two of the three core components of customer lifetime value (LTV), this highlights the crucial role that triggers provide in success.
The role of triggers in virality and retention
Triggers are reminders for people to talk about our product, game or ideas. In Berger’s book, triggers are the foundation of word of mouth and contagiousness. For example, you may regularly show images of your game with coffee, so that people will think about and start discussing your product when they go to Starbucks.
The first step of Eyal’s Hook Model of retention is triggers. Triggers cue the user to take action. There are two types of triggers: external and internal. Habit-forming products start by alerting users with external triggers like an email, a website link or the app icon on a phone. An external trigger communicates the next action the user should take. Online, an external trigger may take the form of a prominent button, such as the Play Now button on many games. When users start to automatically cue their next behavior, the new habit becomes part of their everyday routine. Continue reading “Lifetime Value Part 23: Triggers, the key to both retention and virality”
I am a huge proponent of using analytics and other metrics to drive business decisions, but I repeatedly see people making a huge and avoidable mistake. Instead of using the data to determine the best strategy, they use data to justify their intuition. A good analyst can use data to draw virtually any conclusion and if the analyst is pushed in a certain direction by the business leader, all the data does is provide people with cover for the decision rather than leading you in the optimal direction.
The same situation applies to financial analysis. I have seen people frequently manipulate numbers, often with the approval or even encouragement of the target audience, to tell the story people want to hear. I have seen this manipulation in sales, in corp dev and in internal forecasting. In all situations, it is actually just a rationale to make a decision the person already wants to make.
The first part of the problem is manipulating the data. I am not talking Enron here, but more subtly and maybe not even intentionally. People will often select the data that supports their position while discounting the other information. If you want to greenlight a certain feature, you may look at the impact on retention while neglecting the impact on monetization and rationalize it by saying it is a retention feature. Regardless of whether it is a retention or monetization, your goal is to optimize lifetime value (LTV) so you need to look at the data holistically. Continue reading “Changing the numbers does not change the reality”
For those of you who foolishly decided to take a vacation this summer rather than stay at home and read my blog, I wanted to summarize what I feel were my top ten posts this summer (and below will also summarize the rests of my posts since I am sure you will want to catch up on all of them). Continue reading “My top ten summer posts”
A key to predicting and effectively using customer lifetime value (LTV) is to take a long-term view of your data and not just rely on the first month or even first few days. Many marketers will draw conclusions about a new product launch, a new feature or a unique customer cohort based on the initial data they generate. While you cannot wait months or years to make crucial business decisions, understand that these predictions are less reliable and thus making decisions based on this data is problematic.
While intuitively more data is always better, there are challenges involved in looking back over a long period. First among these challenges is customer attribution. If you are determining the value of a specific growth channel, do you credit the lifetime spend of a user to the channel you used to acquire them initially or do you attribute the revenue to a channel (Facebook feed, email, A2U notification, etc.,) that brought the user back after a long period of inactivity.
The second issue is the sheer quantity of data. If you have millions of customers or players and years of data, it becomes quite a challenge to process all of that data. You may have multiple interactions with that user every day, literally for years. Think of how you interact with Amazon and consider they track all the products you look at, how often you visit, what you purchase, what you purchase instead, etc. You need the software, data warehousing and systems so that you can actually analyze this data quickly. Continue reading “Lifetime Value Part 22: The need to take a long-term view”
I recently read an article on Sociomantic, “Customer Lifetime Value in Three Dimensions,” about looking at lifetime value (LTV) tied to the customer journey and it adds another dimension to calculating lifetime value that could greatly improve its predictive value for you as well as pointing to areas for improvement. The article breaks LTV into three dimensions: recency, frequency and profitability (Note: The authors refer to the third dimension as “monetization.” Based on my previous posts on monetization, I felt this term would confuse my readers, as our definitions differ).
The article points out that a key determinant of recency is when the customer last made a purchase (or in a game, last monetized). When examining the recency dimension of your customers, you should analyze which cohorts purchased which items. With this information, you can then predict subsequent purchases, including what items each cohort (actually each customer) is likely to purchase. This analysis provides an LTV for each cohort (or even customer) and can power a machine learning recommendation engine or post-purchase retargeting engine that would increase LTV. Continue reading “Lifetime Value Part 21: 3D LTV”
There was an article recently that cited a study from Econsultancy and Sitecore that highlighted what companies and advertising agencies are doing across multiple industries to increase customer lifetime value. I have written many times about the importance of lifetime value (LTV), and how it is the core of whether your company or product is successful. The article points out that 75 percent of global company marketers agree that LTV is crucially important. I think it is important to understand what companies in other industries are doing to optimize lifetime value so rather than just following your peers, you can build an advantage over them.
A single customer view
The most common response when asked, “What is the most effective tool to optimize LTV ?” was a single customer view. The recognition that key insights are being missed also supports recent findings showing that marketers are struggling to develop a holistic view of their customers. For example, you may have data from inside your product how consumers act, survey data from your users, focus test results and feedback from customer service. What you may not be doing is integrating all of this data to understand the customer experience and their frustrations. Many companies just look at the in-product metrics but by looking at the data holistically you are more likely to find the levers to optimize best your product. Continue reading “Lifetime Value Part 20: What others are doing to optimize lifetime value”
As this is my nineteenth post about customer lifetime value (LTV), I obviously think it is very important, but I wanted to take some time to provide examples of how it can impact almost any business. Even if the examples do not cover your initiative, they will hopefully help you see how understanding, marketing and designing for LTV is crucial to any company’s success. Examples range from tech companies to business types that have been around longer than the United States. The breadth of companies that LTV is critical for shows its central importance.
Mail order catalogs
Catalog companies, from the days of Sears and Montgomery Ward, to the current heavyweights like Restoration Hardware and Crate & Barrel, have always needed a deep understanding of LTV to succeed.
With the cost of printing and mailing catalogs, these merchants need an LTV higher than the shipping/printing costs. Thus, they have to first understand different customer segments (e.g., location/postal code, sex, age) and only send catalogs to those people who will have a higher LTV. If they sent their catalog to everyone, the average LTV would decline and make their efforts unprofitable. In addition to understanding the LTVs of each segment they have to optimize along the three key LTV variables: Retention, monetization and virality. If a person reads through the catalog once, makes an order and never picks up the catalog again, it is hard for their value to be higher than the costs of shipping them the catalog. If they, however, keep the catalog and place ten orders in a six-month period, the LTV is likely to exceed to costs of sending them a catalog. Monetization is also critical. If they love the catalog, keep it on the coffee table, but never make a purchase, the merchant loses. Even if they make very small purchases the merchant proposal loses. Successful direct marketing companies succeed by getting larger shares of wallet from their customers. Finally, virality is important even for a non-digital good. If the person shows the catalog to ten family members or friends (who have an equal potential to buy), then the costs of sending a catalog are effectively one tenth as you are reaching 10X people. Continue reading “Lifetime Value Part 19: Applications of LTV in different business types”