Are you running a B2B sales or inside sales organization?
Do you have a freemium or free trial in your service?
Are you considering a low or zero touch sales model to increase velocity of your sales funnel?
These modern sales models are somewhat evolutionary as the official enterprise sales model is just not the customers first choice anymore.
Today, in my last “Best of 2011″ post series, I’ve gathered all the videos and posts from which you could learn about low and zero touch sales models and about free trial and freemium best practices so you could go ahead and build your ultimate sales machine!
So how do you know which sales model is best for you – zero touch vs. low touch vs. high touch vs. field?
In his last tip from the Sales 2.0 Convention, Mark Roberge, VP Sales at Hubspot explains that it’s really depends on your buyer, what you’re selling and the full sales context and it does require some experimentation.
Preferably you should aspire to go on no touch or low touch as possible as the economical will always be best if you can pull that off.
But it is best to simply run experiments – set 100 leads to no touch and 100 leads to low touch and check the conversion rate, revenue, Customer Lifetime Value and in SaaS see what the CAC to LTV is (Customer Acquisition Cost to Lifetime Value) and what the payback periods are and take the approach which has the best economics.
Furthermore, as mentioned in many of my previous posts, it is highly recommended to keep a thorough and updated Cohort Analysis for your metrics so that user behavior would come out accurately. This is the only way a successful SaaS business could reach the right consequences and choose its suitable sales model!
Yes so, zero touch versus low touch versus high touch versus fields, the quick answer is it depends, unfortunately, and I’ll walk through the dynamics. It really depends on your buyer and what you’re selling in the full sales context. And it’s gonna require some experimentation. I think in general you’d prefer to go as no touch or low touch as possible.
I think the economics will always be best if you can pull that off. But hey, if you’re wondering, “Here’s a lead that has 50 employees in this particular segment. Should this be a no touch or a low touch or a high touch?” You run experiments. You send a hundred leads like that to no touch, you send a hundred leads like that to low touch, and you see what the conversion rates are, you see what the revenue is, you see what the lifetime value is, in a SaaS role you see what the LTV to CAC and the payback periods are, and then whichever ones have the best economics, you take that approach.
In the next couple of weeks I would like to share some short video interviews on relevant subjects taken at several events I’ve been to.
At the Enterprise 2.0 Conference, I’ve met Eric Montoya from BadgeVille and interviewed him about the ways to convert from visitors to signups and from freemium to paid users.
These topics are highly relevant to every SaaS business and I’ve been writing a few posts about it lately, including my previous post.
In this interview, Eric explains how the conversion process become a simple mechanism when you find unique and fun ways to get your users to know your product by gentle guides or creating a feedback system that is presented back to the end-user once they conducted a series of behaviors that we wanted them to.
Eric also gave some interesting examples in which he mentions a 500% lift for a unique application of Samsung – view the interview to learn more
Tomorrow I will upload another interview from the Enterprise 2.0 Conference. This time Jessie Wilkins, Director System of Engagement for aiim will talk about how the document system era evolved to the system of engagement era.
To read the full transcription of the video, click here
“My name is Eric Montoya, I am with sales and business development here at BadgeVille. You know, there is a couple of really, really unique things that happen within the context of any sort of online community or any sort of interaction with the product, the first is some sort of anonymous or local capture, right?
How do i get that person who has just come to my platforms, to my products and my brand and what can I do to try to capture them at that point? How do I convert them, maybe from fremium to paid and all of those mechanics that go along with could be something as simple as a mechanism like gentle guide or something where I am taking a series of behaviors or actions and presenting that back to the end user in some sort of unique, very step oriented, fun way with that getting feed back as they through all of the interactions learning the platform, taking a steps in necessary to become engaged within the product, but they are doing it in a way that’s very controlled and really wrapped around the behaviors and the actions that you want dozen users to perform.
Us, like our kind of broad, you know, 100 plus customers that we have now, we’ve seen, you know, strategic impact to the goals and objectives tied to a lot of those specific behaviors in the, like, 25 to 30% range, if you want to be very broad.
When you look at very, very unique applications or specific behavior such those users are performing. Samsung, for example, has just put out this last week that they are seeing a 500% lift on some of the drive and user engagement and actions that are very relevant to the success of their community.
Things like rating and reviewing and interacting with the product and the brand overall. So, you know,we have seen a lot of variance but the impact, you know, whether that’s 10%, 50% or 500%, absolutely the numbers are there.”
Eventually, Jason recommends performing cohort analysis when looking at cancellation rates. He suggests to divide customers in segments based on their “time to cancel” (i.e. cancelled after 30 days vs. cancelled after more than 30 days) and, for all intends and purposes, he recommends focusing in the long-term users who have greater business revenue potential and cancellation reasons which can be addressed and resolved more easily.
This is indeed an interesting way to look at it, and very analogous to the importance of the “time to convert” metric when it comes to inbound marketing and trial conversion. However, I argue that this is not the only, and maybe not always the best, way to do cohort analysis on SaaS churn.
Let’s take for example an email service application. If 2 users have signed up at the same time:
One of them is using the service more frequently, creating many accounts, visits almost all application features and cancels after 10 days
The other accesses the service 3 times a week but just checking very limited features and cancels after 31 days
Who should be given more weight?
If I’d measure by Jason, I would focus my efforts on the second user, but if I weigh my analysis with user behavior altogether, then my most valuable customer to understand is the first one.
So this leaves us with three promising ways to segment customers for cohort analysis:
Traditional way: create cohorts based on the week or month in which they signed up for the service. This will allow you to analyze the effect of changes you made to your product or service over time.
Jason’s way: to create cohorts based on the “time to cancel” (or the “time to convert” for that matter). This will allow you to focus on long-time users of your product and sift out those who signed up in error.
The customer engagement way: to create cohorts based on the “engagement level” with the product or service. This will allow you to focus on frequent users of your products, independent on how long it took them to cancel, but still sift out those who signed up in error (and never started to use the product).
Of course, in all cases, measurement is just the first phase of the process and the complementary phase must be to prioritize the changes needed in the service which would ultimately lead to increase customer satisfaction and customer engagement.
What about you? What is your definition for cohort analysis?
Following Lincoln Murphy’spost on SixteenVentures.com (talking about conversion average rate for free trials, pricing pages or Freemium for SaaS or Web Apps), conversion rate average figures will do no good, as it doesn’t reflect the whole picture and usually lacking context.
It’s hard to know what metrics are being used for the “average conversion rate” and Lincoln claims that looking on average numbers to plan businesses around might make us average ourselves – and who want to be considered average?
Every company aspires to increase their conversion rate figures but Murphy’s suggestion is to figure out where you are today and then figure out how to make it better.
Meaning, if you’re at 1% conversion rate, reaching 2% is achievable, even though it’s 100% increase over what you have now.
I agree that context is crucial and also explained about this in “Measure trial conversion rate” webinar. Furthermore, in order for each SaaS business to understand where they stand, a lot of other metrics need to be taken under account besides conversion rate from free to paying customers. For example – do you also review unique visitors to your website? Social media mentions? signups, churn rates, customer lifetime value, account activation rate, account usage statistics, etc.?
All of these are metrics that should be taken under consideration in order to reflect the whole picture for a SaaS company and to allow it to set its goals.
Which metrics do you use to make your goals setting?
Use an inside sales team to support leads through their evaluation process and convert them to paying customers.
Inside sales representatives (ISR) and sales management teams juggle with large volumes of leads of various qualities. Leads follow a self-paced evaluation model and the role of the inside sales team is to increase the number of those that eventually “convert” to paying customers once their trial concludes.
Here are 4 tips for inside sales teams to improve their effectiveness, increase conversion rates and deal sizes. Creating happier customers and a happier sales organization!
1. Prioritize correctly by eliminating noise
Within many SaaS companies the lead volume is very high and there are only so many phone calls one can make. The trick is to focus on the most promising prospects, the potential customers who came in with a real intention to evaluate the service and buy.
In order to focus on the right opportunities, sales teams should have ‘intention indication’ which is usually reflected by the amount of time and investment prospects put in the evaluation process. In short, make sure your CRM contains data that reflects the actual (as opposed to potential) engagement level of a lead, and prioritize your work accordingly.
2. Increase Contact Rate
Every sales person knows that being in contact with a prospect increases the chances of a bigger, better deal. However, in many cases, due to volume and geography it takes a while before you can actually contact a prospect.
To increase your chances of making contact, follow up while the prospect is within context, meaning, when the prospect is actually using the web application. By implementing a ‘who’s currently online’ monitor and contacting leads that are actively evaluating, your contact rates are sure to go up.
3. Make smart and personal sales call
When making contact, be sure to use all the information you have on the prospect in order to be personal and address the actual needs of a potential client. Prospects who interact with your business over the web expect a conversation with a sales rep to be effective and rather not repeat their entire history which was already reflected in forms that they have filled out and actions they performed on your application.
Make sure to prepare for each sales call by reviewing the following on the lead:
Demographics information: This includes the size and industry of the organization, the evaluator’s role within the organization and so forth.
Usage information: What has a prospect done so far during their Trial? Have they been able to get up and running? Are they using the software regularly during trial? Did they invite necessary stakeholders to join the evaluation (where appropriate)?
Make sure your sales-tools provide visibility into these two issues so you can form an intelligent view on their status and be more useful to the lead as you interact.
4. Timely follow up
Potential customers need time to absorb the information available on your web site and properly evaluate to understand the true value of your service. In many cases, they will evaluate multiple alternatives simultaneously. Make sure to follow up on time. On the one hand you don’t want to annoy the prospect (that adds zero value), but on the other hand you wouldn’t want to drop the ball and let them fall in the hands of your competition.
Sales teams should map various milestones of the evaluation process, and have clear benchmarks and definitions for prospects who are on track and those who are not.
For example, for an online help-desk service, we would expect to have more than one agent by the 5th day of the evaluation. If this is the case, a prospect is on track and only needs encouragement, if this is not the case, a prospect might need a different type of engagement in order to open the road blocker.
Managing these milestones for multiple ongoing accounts is not easy, but it’s essential to fulfill your role as a facilitator of the evaluation.
Successful SaaS sales teams that follow a proven methodology and take advantage of automated high-quality information will increase their chances to sell more and faster. They will improve the predictability and consistency of results – this is critical for scaling the organization.
Managing a Software-as-a-Service (SaaS) business isn’t trivial. Successful SaaS companies are able to deal with a high volume of leads and turn those into a high volume of loyal customers with fast response and turnaround time.
This is often referred to as the ‘sales and marketing machine’ – a highly optimized, massively scalable and controlled business operation that is capable of:
Continuously increasing the service value, differentiation and offerings.
In order to build a ‘sales and marketing machine,’ companies need to invest in the tools that will get them the business scalability that is required and reduce the learning curve.
Many startups begin with homegrown solutions using spreadsheets and databases (with a bit of integration glue in between). This is sufficient for small scale, but quickly becomes unwieldy as the organization grows. Luckily, there are excellent tools available for SaaS companies to leverage.
Many vendors have a “starter” package, so there is really no excuse not to start building your tool-chest sooner rather than later.
The Customer Life-Cycle
To best understand where the different categories of tools fit, it’s best to look at the various stages of the customer life-cycle, as they evolve from early prospects to mature customers.
At Totango, we use the following customer life-cycle terms:
Visitor – Anonymous user on the website
Lead – Person who has expressed some interest in the service. This can be anything from downloading a white paper to signing-up to a trial
Evaluating – A user (or company) who’s actively evaluating the service usually during a trial period or fermium
Onboarding – A paying customer in the initial usage period
Mature – A paying customer who has been loyal to the service beyond the initial usage period
With those definitions in mind, it’s easier to associate solutions and tools to help carry customers through every phase of their life-cycle.
CRM (Customer Relationship Management)
CRM is a common way to keep a reference of all customers’ life-cycle stages. CRM organizes all contacts’ information and account details in a single database, so it’s vital you select a tool that fits your needs and can grow with you.
Specifically, your CRM software will be the main working software of your inside sales teams as they organize account work mainly during the sales life-cycle phases.
Web analytics tools keep track of visitor activity on your website and various other marketing properties; this is where you keep track of your top-tier leads funnel, measure the initial success of marketing and advertising programs, and work to improve visitors’ experience with your products’ properties.
Mainly the marketing team, though other users in the organization (product team, IT) will need to use it as well.
Select list of Web Analytics solutions Google Analytics is the most commonly used tool. It’s immensely powerful, feature-rich and free. But there are other good tools your marketing team should look at, such as Clicky, WebTrends that provide additional useful views into vistiors’ actions.
Marketing automation takes you beyond basic web-properties and aims to help you interact, build, and cultivate a relationship with leads, so they can ultimately be passed on to your sales team and “convert” to happy customers.
This is your marketing team’s main toy!
A post marketing (sales & customer success) solution stack for SaaS companies does not exist yet. Enabling the buying process (converting leads), ensuring customer success, and increasing service value, is something that I feel is needed and missing in the market, and this is what we’re building in Totango.
Having all the above tools in place enables marketing, sales and customer success teams to effectively do their jobs and be an integral part of the ‘sales and marketing machine’.
Having said that, it’s crucial to have a single business dashboard available to the executive teams that allows them monitor the business end-to-end.
The SaaS dashboard should include operational metrics, trends and key business performance indicators (KPI’s), which allow the business owners, get ‘the full picture’ of the business, identify bottlenecks and allow to teams to take appropriate actions.
The SaaS model presents an opportunity to run a predictable and high-volume business. The first step is to put the required business infrastructure in place in order to monitor, analyze and optimize the sales and marketing machine operation continuously.
In coming posts, I’ll discuss in further detail the actual attributes of the SaaS dashboard.
Trial conversion comes from multiple business processes: from sales, to marketing, to the product itself. In order for metrics and collected data in general to be valuable to your company, they must be actionable and this will mean different things to different aspects of a SaaS business.
For sales teams, it’s all about focusing on opportunities that matter most in your business pipeline. For the majority of SaaS sales teams, there are many more leads than the team can effectively handle. The team needs to be able to focus its energy on those that are more likely to convert into a sale.
Once you are working with reliable conversion rates and have eliminated the noise in the funnel, your sales team can use the same process to prioritize its work. Rather than contacting, qualifying and trying to convert all new trials, they should focus on those that appear to be “Actually Evaluating,” as those provide a much more likely sale.
One of the key challenges for the marketing teams of a SaaS company is the need to properly qualify leads. The nature of Internet marketing is essentially casting a wide net into the unknown and trying to engage with as many people that are relevant to what you have to sell. The reality though is that you end up also engaging many that are not really relevant to your offering. Understanding the ratio between these two groups is essential to figuring out which marketing efforts are effective for your business. The ratio between effective (i.e.. “Actually Evaluating”) and total leads represents this exact number. This ratio is essential when determining if your marketing strategy is working and if your budget is well spent.
The ratio number will naturally vary by industry, but you need to make sure it’s under control, i.e. the number of qualified leads should constantly be growing; this will essentially lower acquisition costs (a fundamental parameter in business sales of a SaaS company).
People that signup to your trial are primarily there to experience your product and assess it if fits their needs, and they expect to be able to do that quickly and with minimal effort on their behalf.
That means, someone who comes into the trial immediately gets it, is productive in attempts to evaluate product, has all the information they need, and the product’s general usability and experience is of high quality.
How to improve the product experience for your customers is something your product team needs to constantly assess (see “Getting your prospects to be come devoted users” provides solid ideas). But the key metric they should use to determine if they are making progress is conversion rate. What percentage of qualified leads ends up activating they account, using it and eventually upgrading to a paid account.
Data, when correctly measured and broken down into proper categories, becomes valuably actionable. Keep in mind that this activity is not a one-time effort; it has to be ongoing and continuously improved. The business needs to be able to measure data effectively, get the information in front of the right people at the right time, and constantly improve those metrics based on their true meaning.
Next week we’ll jump into understanding marketing automation, BI, analytics, and CRM.
To learn more about Trial Conversion please View our Webinar where we discuss Best Practices in Measuring Trial Conversion Rates for SaaS Applications:
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Over the next few weeks, Totango will be posting a blog series on best practices for measuring conversion rates of trial usage for Software-as-a-Service (SaaS). Trial conversion is arguably the single most important business metric for SaaS companies since the model is based on two key parameters: customer acquisition cost and customer lifetime value. The trial conversion moves customers from the acquisition phase to the lifetime value phase and as more potential customers become paying customers, the customer acquisition cost goes down and the customer lifetime value goes up. Simply put, the ratio between customer lifetime value and customer acquisition cost is the entire profit of a SaaS company.
It is important to make sure that the measurement of trial conversion addresses three basic concepts:
Simple to measure;
Simple to understand;
Unfortunately, trial conversion is not that simple to measure correctly (most organizations do it, but haphazardly) because there is no “single source of truth” per se. That is, trial conversion comes from multiple business processes (marketing and lead generation, in-house sales, and the product itself), which muddies the ability to measure it definitively. As a result, to get an accurate trial conversion number, organizations need to make sure that all the data collected is aligned among the business processes mentioned above.
The second challenge is “noise,” or trials that are “dead on arrival.” These users may have signedup for a trial, but have no intention of buying. They are just playing with the software because they can; it could be for educational reasons, it could be for other reasons. Taking these “dead on arrival” trails into account creates a very blurry picture, which is difficult to take action on.
Considering the challenges of measuring trail conversions (and the need for simplicity), the first step is to define the active, or effective trials (trials who came with the intention to buy and now are evaluating the service) and weed out the “dead on arrival” trials. There are different ways to do this of course, but one example could be measuring active trials based on a second day of usage or perhaps based on what the user is actually doing. Once the SaaS organization defines an active user, a baseline can be established. A baseline is taking the current number of trial conversions (and perhaps taking into account historical information as well, if available), and setting metrics around that.
With a baseline set that weeds out “dead on arrival” trials, organizations can tweak the service they sell or the various parts of their sales and marketing processes to improve trial conversions. Perhaps the organization needs to focus on marketing to get better leads because the current leads aren’t good enough. It could be that the sales process is not effective and it needs to be improved. Or it could be that the service itself needs improvement. Ultimately, the SaaS organization needs to measure continuously in order to put a finger on the right problem.
Imagine an organization that had, for the duration of July, 1,000 new signups for trial. Out of those accounts, 10 ended up “converting”. On the face of it, the conversion rate is 1%.
However, dig a bit deeper and in many cases, you see that many, if not most, of those 1,000 trials never had a “buying potential at all”, evident by the fact that they never did a serious evaluation of the service
(note: it would be nice if numbers in real life would be so round and simple to calculate in ones head!)
Why is this important? First off, because it gives a more real indication to what is going on within the sales team’s pipeline (they are succeeding in selling to 1 out of every 10 prospects not out of every 100), and it is easier to motivate people to improve a metric they intuitively feel is true.
But that is not it, in our next post, we’ll explore what the trial conversion metrics mean and how SaaS companies can best act on the data that is collected to increase conversion rates.