Any software as a service startup is a massive opportunity for a marketing technologist to provide value as an employer or a freelancer. Follow along to discover the ways that I provide value with marketing technology for software startups and how you can too!
What are Software Startups Missing Right Now?
Software startups are becoming incredibly popular due to their recurring revenue models and high valuations.
Due to their focus on data, software startups have massive gaps in marketing technology problems that any marketing technologist can provide massive value on. Here are the gaps in marketing technology for software startups.
Within software startups, departmental silos can be your kryptonite. Since the entire relationship from sales to customer success and product are cyclical, having miscommunication or lack of visibility can be brutal to a company.
Marketing needs to learn from sales and improve revenue, not awareness.
Sales need a way to build data that transforms anecdotal data into insights over time.
- Are we losing to competitors? Why?
- Can we automatically log this information in any way?
Customer success needs to be an extension of the product.
Without the right data flowing, silos block the healthy flow of communication and growth.
Playing Moneyball with their company
With most software startups, you see investors get better metrics than the internal team.
This is an opportunity to arm the internal teams with enough data and insights to perform at a higher capacity.
When you track internal numbers about the efficiency of the process like sales cycle or churn and visualize it for your team, you allow them to notice subtle changes in their process and contributions.
From there, they can start using data to their advantage on the revenue side, not just the product end.
Investing in processes and systems
Solving problems with more employees will never work no matter your size.
A new salesperson takes 5 months on average to ramp up.
Marketers take about the same time in the best-case scenario.
It is better to invest in processes and systems first before throwing employees at the problem.
Below are the 4 highest impact projects you can work on as a marketing technologist at a software startup.
Sourcing leads & scraping information
Salespeople spend 8 hours per week researching
Even if you sent lead sourcing purely to Upwork, you would have a 6.89 save in budget, not to mention the ROI. Why do companies not invest in their teams then?
What could they be doing with that time if they had all the information they needed?
When you had a team of 6 salespeople, that’s 48 hours leaving the sales process a week and 192 hours a month.
- Google the web automatically
- Scrape industry websites for intent data
- Scrape Twitter
- Use the Yelp API.
If your company pays an average of $100,000 per sales rep, you have now saved them 384 hours per sales representative. In a 2,087 hour work year, you are saving 18% of their salary or $18,000 a year per rep.
That is a massive amount of value from some simple scraping.
Syncing CRM with Your Product
Often startups are split into two major categories:
- Customer Success
While this makes sense, it opens up a major gap: Your customer success team isn’t an extension of your product.
Here’s the solution: Arm your team with recommended actions, not data.
With this data, your customer success teams can do the following:
- Build hyper-personalized account management in your CRM.
- Anticipating needs to increase revenue and decrease churn.
- Create account management templates.
- Create triggers when a client is being neglected.
With this information, your team will be an extension of your product, not just the support team.
Predicting Churn & Tiering Customers
Churn is the most important metric in a software startup. It does not matter how much you sell if you cannot keep those clients.
Here are my steps to reducing churn as a marketing technologist.
- Identify what has the largest effect on churn so you can address it.
- Predict the probability of churn per customer.
- Tier customers to identify which clients likely the churn are the most important to spend money to save.
- Create cohorts and split tests to identify if intervention improves retention.
Identify Churn Reasons
The first step to identify churn before it happens is to identify the reasons that it occurs.
There are 2 ways to do this:
Ask Your Customers Why They Cancel
When users cancel their subscriptions, make sure to add a field for them to tell you why. The more that you can bucket these options, the better. It is never helpful to have 40% of your cancellations say the reason was “Other”.
From there, you can see the percentage of why people are churning.
If you have a lot of untagged cancellations, consider having customer success team members email your past users and ask why they churned along with a survey. You can expect a 15% response rate on this. Remember, some data is better than no data.
Use Data to Identify Churn Reasons
If you have access to the underlying data of your product, you may be able to run a churn regression to identify the core reasons that clients churn.
This is best done through a Logistic Regression where 1 signals a canceled user and 0 signals an active user.
From there, you can run the Logistic Regression with your data points and pull the multipliers to see how much that feature impacts churn probability.
Some variables to include in your regression might be:
- Days of inactivity
- Average time between action
- Total revenue
- Number of users for a company
- First support rating
- Last support rating
- Average support rating
Come up with the variables you think impact churn and be shocked by which ones are mission-critical and which ones aren’t.
Predict Churn Probability
If you went with the data method to identifying churn reasons, you now have a list of numbers that indicate the probability of churn.
You can use this logistic regression ( after testing it ) to predict churn.
It is ideal to leave this as a probability score from 0% to 100%. You can then allow customer success teams to take their own action or set up automated cadences when the score gets above 70% or 90%.
This can empower your team to take action before the dreaded cancellation email comes in.
Knowing which customers are most valuable to your customer can help you prioritize support, create processes, and track churn better.
The best way to do this is through RMF clustering.
This stands for Recency Monetary Frequency. Here are the definitions:
- Recency – how long has it been since the last customer action / purchase?
- Frequency – how many times have they performed this action / purchase?
- Monetary – how much is this customer worth to us in revenue?
Once you have that score, you want to bucket them into groups of 3. I prefer to use clustering since I’m technical in nature, but you can find a number you think makes sense.
You then want to add them all up from 1 to 9 and create three groups.
You now have 3 tiers of your top best customers, medium customers, and your least valuable customers.
You can then identify what vertical makes up each tier as well as other data points to form an ideal customer persona that is even more exact.
The final step of churn prevention is to create ongoing cohort analyses. You want to know that your customer retention efforts are improving over time.
You will create small cohorts by month or week to track their retention week by week or month by month.
From there, you can visually notice if a certain cohort is performing worse than the cohorts from before.
Bonus: Add a weekly note to each cohort on what experiments you are testing to increase retention. It is always helpful to know what increases and reduces retention.
How do we measure success?
As a marketing technologist working with startups, you need to be able to measure your success and contributions to the team. Here are the metrics I measure to show that the company is growing efficiently.
Sales Cycle Reduction
Telling a sales team to sell more deals is pretty unreasonable if you don’t consider how long it takes them to close a deal.
By measuring the sales cycle, you can baseline how long it takes to close a deal and show improvement over time.
Higher conversion through the funnel
Tracking conversion rates between certain steps of the funnel allow you to show progress over time with much more granularity.
By separating the sales funnel into multiple steps and stages, you are able to identify what bottlenecks are being created.
When you combine this with historical data, you can identify the issues in the funnel on a rolling quarterly basis.
Lower Touch Points per meeting & close per quarter
It usually takes 7 touchpoints to close a deal. While that is the average, that doesn’t mean it is stuck there.
Many variables affect this average like the following:
- Email Sequences
- Lead Source
By identifying these variables that affect difficulty in selling, you can identify large bottlenecks for your sales team and clear the path for the easiest clients to close.
Higher Average Selling Price
Depending on your company, you may offer multiple pricing packages for monthly recurring revenue. This is where the Average Selling Price can show you how receptive your customers are to your product and how much on average the market is willing to pay.
This is a critical value for product-market fit and how well your team is performing.
Tracking the percentage of revenue that comes from expansion can show you how much your clients enjoy your company and product.
This can be an important metric that shows how much revenue is being replaced by expansion compared to churn. The hope for your company is that your expansion revenue offsets your revenue churn per month.
You can break this down by product to find what product lines promote the most expansion.
Reduced churn for Tier 1 clients
Now, we start using our tiers to segment our metrics and bring focus to our company.
By focusing solely on churn by tier, we can identify whether we are focusing enough on the users that bring all the revenue for us.
This allows us to see how well over time we are prioritizing our top clients and ensuring they do not churn.
More tier 1 clients percentages
As we grow as a startup, we want to make sure we are attracting more ideal customers based on the ideal persona.
This will makes sure we keep our focus on the right customers. This percentage metric allows us to keep up each month on our ideal customer saturation.
Bonus: You can use Tier 1 customers in your commission structure to payout higher commission for higher tier customer types.
How much revenue are leads generating?
When software startups generate revenue on a monthly basis rather than a contract basis, it can be difficult to judge marketing leads for the revenue they are generating.
By tracking this information in the CRM, we are able to identify which channels are performing the best between:
- Organic Search
This information keeps marketing accountable to their revenue numbers as well as their churn. If you simply value vanity metrics like leads, you will optimize for the metric at the top while not analyzing the true value to the company.
A lead from LinkedIn could be more expensive and produce less revenue per month, but churn at a lower rate compared to a Youtube ad that is cheaper and produces more, but churn in 2 months.
Not all leads and customers are created equally, so it is important to check the data to see which is truly profitable.
Conclusion on Marketing Technology for Software Startups
Marketing technology can provide massive value for software startups. From reducing sales research process to creating detailed churn analytics, marketing technology has the opportunity to help software startups grow significantly.
If you are not interested in software startups, you can apply many of these solutions to other industries. Discover which marketing technology niche you should choose.