Using Red Flag Indicators to Fight Churn

The most important thing to a customer success program in any company is that it keeps the figure representing this rate as low as possible. Of course, the CSM team can do all it can to prevent churn. However, that’s not where the real challenge lies. Once the churn has already crept in, as it inevitably will, how do you fight it? The real problem with this is figuring out why your customers are forsaking your service.

Once you know clearly why users are leaving your subscription base, you have half of the problem already solved. Now it just becomes a matter of plugging a few holes and keeping customers happy.

One way to efficiently track the causes of churn in your product is by using red flag metrics. This is mainly the process of tracking user behavior in a bid to find out where their behavior starts to change and become indicative of abandonment.

The Writing’s on the Wall

Before a user ever leaves your product and decides they won’t be logging into their account again, they show signs of the same. Most users won’t wake up one morning and suddenly decides to abandon a product. It is usually a slow process of frustration or indifference that culminates in abandonment. Your job as a member of the CSM team is to find patterns in user behavior to see these red flags before the user capitulates.

The signs are usually easy to see. The first thing to go out the window, of course, is engagement. What was a casual login every day turns into a login every other day. It soon becomes once a week, then once a month and before you know it, the user is missing in action.

Such signals are what we call red flags, and they are essential as they enable us to see the smoke before the fire begins to burn. Once you start to recognize at the red flags waving, you can quickly remedy the situation using various tools, including automation on a large scale or contacting the customer directly. You would be surprised at the difference made by a popup tooltip, or an automated email can make.

There Are Many Different Types of Red Flags

There isn’t a one-size fits all list of red flags that you can look for. Everything depends on the specifics of the situation; your product, the type of customer, as well a lot of other small details that come into play along the way.

The best way to find red flags is to work backward. Look at clear-cut examples of customers leaving your book of business. These are customers who you are sure to have entirely given up on your product. Try to find the common thread running through all of their cases. You can also look at other issues, such as:

  • Customers who haven’t opened your app in a long while
  • Customers who have given your product scathingly negative reviews
  • Customers who have recently uninstalled your app
  • Customers who closed their free trials

shutterstock_200797052The last one is particularly telling since a majority of customers don’t close their accounts, no matter the service. These are some of the things you can look at to give you a clear indication of who already left and who might only just now be toying with the idea of canceling your services.

To understand why customers are canceling your business, gather the data on a group of customers who have canceled and start to look for trends in their experiences.  It’s important to look for any patterns as they will help you quickly identify potential future churners and rush to fill the leaks before they become impossible to manage. Try to compare their activity, or lack of it, before they left, with the activity of your most devoted customers. This is when the data you collect as a business becomes vitally important. Refer to their history and compare it to other users, with tools like VisualCue, to understand the trends in unhappy customers.

Activation is a Critical Stage

As mentioned earlier, there aren’t any universal red flags to look out for. However, some common signs will easily apply to many SaaS products and organizations.

One of the factors that matter most is how many users manage to achieve activation. The activation point is the point where the user completes the setup process for their account. The truth is, most users do not reach full activation of SaaS products. The actual percentage is close to 60% of users on free trials. These users never log in to their products beyond that first login.

Users can fail to reach the activation point for a plethora of reasons. They might just have decided that they don’t like your product, or you might have targeted the wrong type of user with your marketing strategy. There will be some factors you can’t control, but it is essential to mitigate any factor that leads to churn as much as possible.

When the User Doesn’t Login Again

If your product has an established user base, then there is a clear pattern for most users for how frequently they log in, and it is up to you to understand that trend. The typical user might be daily, weekly, and so on. When you notice a user breaking from this pattern, then that’s a red flag of potential churn. The failure of a customer to log in is an indicator that the customer simply doesn’t see as much value in your product as they did before.

Here the solution is to remind them of how valuable your product can be for them. Send them an email containing reminders for them to check their accounts. You can also send them some educational materials or little tips on how to navigate particularly different areas that they might be having trouble navigating. It’s as simple as getting the customer excited about your product again.

The Follow-up Always Matters

Remember, the point of this whole process is to recognize churn before it materializes and nip it in the bud to reduce your overall churn rate. The easiest method to reduce churn before it starts is to observe patterns as they emerge and employ large-scale automated solutions. Tracking these signs of churn is made simpler with the use of the VisualCue data visualization tools. It can help you see patterns in your customer base at a glance and in real-time, allowing you to be able to understand better where your customers find value.

By looking for the red flags you and acting quickly on them, you can reduce your churn rate and turn business around altogether.

 

  • Sources
  • https://blog.intercom.com/designing-first-run-experiences-to-delight-users/
  • https://glideconsultingllc.com/makes-great-onboarding-process/
  • https://glideconsultingllc.com/10-reasons-saas-business-creating-poor-customer-experience/

 


Understanding Why Some Customers Leave

Understanding why some customers leave is something that many businesses struggle with. Companies small and large have been looking for answers on what they can do to reduce their churn quickly to unlock significant revenue potential. As Benjamin Franklin once noted, “An ounce of prevention is worth a pound of cure.” This idea is the foundation of what reducing churn is all about— preventing small issues from turning into reasons for cancellation.

For the sake of this article when we refer to churn, we will be referencing customer churn rate or the pace in which customers are leaving your book of business. This likely effects your company but if you are a SaaS provider, then this should hit especially close to home. So how can you reduce your customer churn rate now? For starters, you must understand the customer experience from start to finish.

It’s time to get tuned into your customer lifecycle. If your lucky enough to have customer success managers within your organization, speak with them about the signs of a customer who is about to cancel your service. These are the people you should be learning from to better your chances of keeping customers paying for longer. Signs of churn can range from being late on payments, browsing the terms of service page on the application, calling a help number, or even the age of the account. Learn which signs of churn are most important in your business and address them as soon as possible. If a CSM is not readily available for you, use your data to determine common traits of customers who have canceled your service. By monitoring the symptoms of churn, you can better address customer needs before it’s too late.

why-do-customers-leave-a-company-2017Consider this, according to SuperOffice.com 68% of customers leave a service because they feel as if the company does not care about them or their needs. One thing you can be doing right now is reaching out to your customers to understand what they expect from your service. By doing this, they will know that you care about their needs being met and will likely stick around.

caleb-jones-131206We live in a data-driven world, and responsible decision makers understand the power of decisions backed by data. By following and tracking your customer experience from start to finish, you better understand common trends and better address concerns. Here at VisualCue, we offer the tools to see in real-time which customers need attention. With limited training, you and your team can find the patterns in the data necessary to meet your customers’ expectations. Happier customers lead to less churn which leads to more monthly recurring revenue in the case of a SaaS company.

No matter the industry you are in if you are running a business than it is safe to say that you are concerned with keeping customers happier for longer. Reduce your churn rate by understanding the customer experience and look for patterns in the data. As you analyze the data, you will begin to recognize commonalities between the unhappy customers. Find these trends and address them because in the end, if you don’t take care of your customers, then I am sure someone else will.

 


What can you do about customer churn?

Although 96 percent of businesses fail within ten years, some companies manage to become successful enterprises. Companies like Apple, Berkshire Hathaway, and General Electric manage to thrive even though they face considerable trials—but how? What are these companies getting right that so many others are getting wrong? They keep clients onboard.

interview deskThese companies get a few other things right, too, but when it comes to customer retention, they refuse to leave a single box unchecked.

With a five percent reduction in churn leading to a 25 to 125 percent increase in profits, it should come as no surprise that your company can benefit significantly from reducing its churn rate. And with new information and customer retention software that can help decrease your churn rate today, there’s no excuse for not improving this aspect of your business.

Below, you’ll find more information on customer churn, its importance and how you can retain more customers.

What is Customer Churn?

The software as a service (SaaS) industry is primarily responsible for making churn a noteworthy metric. Churn is equal to the number of customers you lose every month divided by your total overall customers. For example, if you have 100 customers and you lose three, your churn rate for the month will be three percent.

Acceptable customer churn rates often fall somewhere between 10 to 20 percent churn per year. Churn standards often vary by industry. For example, SaaS rates are considered good if they’re below seven percent.

One other thing that’s important to note about churn is that the percentages as mentioned above aren’t universally accepted. Although a five percent churn rate might be acceptable to you as a business, venture capitalists and other funding parties prefer churn rates of around two percent a month.

Finding Your Customer Churn Rate

As mentioned above, the most basic way to calculate customer churn is to take the number of subscribers or customers you lose every month and divide that number by your total customer base. Some companies will claim that they have a negative churn rate because they add more customers than they lose every month, but industry experts suggest that businesses avoid this method because it often provides a less comprehensive picture of their consumer retention success.

mrr-churn-analysisChurn can also be calculated with revenue as the baseline. With this approach, companies first derive their monthly recurring revenue (MRR). Then, they take the amount of their canceled MRR and divide it by an interval of time multiplied by total MMR at the beginning of the period.

How to Reduce Customer Churn

There’s no hard-and-fast rule when it comes to what you should and shouldn’t do to reduce churn. Contemporarily, large businesses primarily use the following techniques: they give their customers fewer chances to terminate their relationship, they conduct a survey, or they invest in a customer retention software.

Whether you know it or not, you’ve probably been subjected to the first retention strategy. Companies that enlist this technique start by offering a free trial of their product or service. Once the trial is up, they just bill the free trial user annually. This approach seems to improve customer churn efficiently, but at the end of the day, it might only delay the inevitable. After all, if you’re unhappy with a company, you’re going to stop doing business with them eventually.

Surveying customers is another way to try and prevent churn. Call your customers or send them an email and ask them what they like—and don’t like—about your product. This technique will give you a greater understanding of what causes people to become valuable customers so you can try and replicate their experience. As you get to understand your customer base better, you will begin to learn what is essential to the people or companies you serve and what needs attention.

Last but not least, you can reduce customer churn with the help of a software platform. This is often the preferred approach because it provides companies with more valuable customer churn information than the two other strategies combined. Customer retention software offers real-time data that are key to reducing current churn and preventing it in the future. If this is the route, you take to make sure to study the options you have before you. So tools deliver insights on data while others, like VisualCue, offer actions to consider as you monitor your client base. No matter how you plan to take on your churn rate, remember that, it is best not to wait!


Understanding churn rate

To truly understand a business’s health, company’s track certain numbers. One metric that we feel is vital to tracking and predicting a company’s success is customer churn rate. It can be hard to understand what is causing your churn rate to increase but with a little bit of work and change in focus, you can overcome what seems to be an impossible task of keeping customers happier for longer.

Churn rate is the rate at which your customers are leaving your book of business. If you want to find your company’s quarterly churn rate do the following arithmetic: the number of customers that you lost last quarter divided by the number of customers you started last quarter with. The percentage you end up with will be your churn rate for that quarter. So if you have 500 subscription based customers and 25 of them leave your book of business last month, then your churn rate for that month would be 5%.

jonatan-pie-234237This may sound like an extreme case, but believe it or not, the average churn rate for a SaaS company should be between 5-7% ANNUALLY! That means most companies in the SaaS industry should only have around 0.42 – 0.58% monthly churn.*

It can be easy to fall into the mindset that all you need is new customers but it is vital to avoid falling into this type of thinking. According to smartinsights.com, only 18% of companies put a strong emphasis on customer retention. This is insane given the fact that it costs nearly 5X as much to acquire a new customers than it does to upsell/keep an existing one**. Not to mention the fact that existing customers are much more likely to talk about contract renewal or upsell possibilities.

So how do you keep your customers from churning? There are a few different efforts that can help you get your company on the road to keeping more customers happy resulting in much more revenue.

First, make sure your business model is catering to the needs of existing customers. Don’t be like the 82% of businesses that don’t place existing customers needs first*. Placing new customers ahead of the existing one is a business practice that has to end now. Understand who your audience is and what they consider good service. This might include more check in calls or email follow-ups. It all depends on your business…but above all they need to know you care and that you are listening to them and handling their concerns.

carsten-stalljohann-197892Second, looks for the signs of a customer who is about to cancel your business services. Chances are your business has these numbers and all it takes is the right person with the right tool to see what leads to a customer leaving. Sometimes this is a lack of communication between a business and the paying customers and other times all it takes is a support phone call that lasts too long. No matter the reason, if it causes a customer to leave your business, you should care about it enough to track as a metric.

Third and lastly, be willing to change. Change is uncomfortable. And addressing churn rate can show a lot of weaknesses in current processes. Sometimes the changes needed are not addressed because caring about customers is not baked into the company culture and it might be up to you to change this! It can be a long road for your company to shift concern to a current-customer focus but in the end it is almost always worth the increase in revenue.

If you are a decision maker at your company and you want to make a real difference in the total revenue your company keeps, one of the most effective things you can address is customer churn. It will be a long road ahead to stop customers from leaving your business and it’s services. But don’t let your customers slip away unnoticed and start tracking (and eliminating) your churn.

 

sources: *source – http://sixteenventures.com/saas-churn-rate, **The Harvard Business Review


Interpreting Your Data to Reduce Customer Churn

Customer churn is costing you money. Most times it’s costing you a lot of money! Fortunately, increasing your customer retention by only five percent can increase your profits by 25 to 95 percent. So, you might be wondering how you can convince a customer to stick around. Well, it all starts with analyzing your customer relationship management (CRM) data.

CRM systems have transformative potential when it comes to reducing churn. However, very few businesses understand how to maximize their systems to improve customer success. If this sounds like your organization, you should focus on three areas when you track and analyze churn. After you’ve finished reading this article, you will understand how to identify problem areas and monitor change as you implement strategic solutions.

Analyzing Customer Behavior

Have you ever noticed that some of your customers behave the same way—especially if they have similar characteristics? Particular groups of your customers do in fact exhibit common behaviors.

If you can learn the common behaviors associated with particular groups, you can predict how similar customers will behave under similar circumstances. For example, you can estimate what a customer’s reaction will be to a future marketing action or an outreach moment from a team member.

Luckily, building customer behavior models is fairly simple with the help of a CRM tool. The confusing part is often translating the data into all-in-one visualizations. Many companies work with a data visualization, like we do Visual Cue, to better understand their reports.

Image #1 (1)Another aspect of customer behavior analysis that can challenge companies is deciding how specific the models should be. Businesses that already use software designed to track user behavior can generally make their reports very granular. After all, one of the advantages of a CRM software is that it collects and organizes a plethora of specific user data.

Businesses that don’t have a user behavior software in place may need to work with their engineering team to see if they can provide the data or create a tool that will collect it moving forward. Overall, the more specific you can get with customer behavior data, the better. An in-depth report will take time to produce, but it’ll provide you with the best picture of what behaviors lead to customer success.

Considering Customer Age

Another effective way to analyze customer churn is to look at churn by age. Here, age is calculated by how long customers have been with your company. In other words, one age group could be “first month,” and another could be “twelfth month.” After all of your users are sorted by the amount of time they’ve been customers, you can start to analyze customer abandonment rates.

Viewing data in this way will help you grasp customer information in a simple way. It will also allow you to know your customers’ behaviors as they age. Chances are you will notice some similarities that you can try and address.

Companies that have high churn rates within the first few months can and should be working on improving their onboarding process. On the other hand, businesses that notice increases in churn several months in might find that their rates increase when customers need to renew their contracts. If spikes occur during specific time frames for various reasons, and addressing these reasons can make all the difference.

Risk_Pg11Once you implement solutions to problem areas, take the lessons learned there and apply it to another problem area in your business. Step by step you will be able to conquer all the issues your company faces.

Churn By Time Frame

In some ways, analyzing churn rates by time frame is similar to analyzing churn rates by age. The main difference is that time frame data can be harder to track and analyze—especially if you’ve been in business a few years. Again, this is why many companies work with a data visualization tool or software. It’s all too easy to become confused by a chart that has hundreds of lines.

To group customers by time frame, you must first define your parameters. There are several common ways to do this, but one of the most popular is to group customers together my month. Under this parameter, all customers who purchased in January of 2017 would be grouped, all customer who purchased in February of 2017 would form another group, so on and so forth.

When you analyze data based on time frame, you’ll notice two benefits right off the bat. First, you’ll find that your numbers aren’t influenced by customer acquisition. You’ll have clean, clear data that speak only to your customer abandonment rates. The second benefit is that you’ll see clear patterns for various groups.

After you create this report, analyze patterns and look for causes of customer churn. If you find that a lot of customers joined your company in November but abandoned shortly after that, seasonality might be to blame. With this speculation in mind, you can begin to look into what happened in the month November to learn why that time frame group had a high churn rate. As soon as you figure out what led to the increase in abandonment, you can create a plan to improve your retention for the future.

This type of report may also provide you with insights on actions that improved customer retention. For example, if individuals that joined in April have lower attrition rates, chances are you did something right to influence them to stay with your organization.

Once you dig into the month, you can begin to determine the elements that incentivized customers to stay active. Then, you can work on reducing churn by creating similar conditions for your entire customer base.

The Impact of Reducing Customer Churn

There are many ways to make reports, but every single one you create should inform strategic action. Overall, the easiest way to interpret data is a clear and accurate visualization that will help you gain insight into your customer base.

Equipped with strategies to collect and represent your data, you’ll be able create plans designed to influence churn. You might instruct your marketing team to run campaigns that share similarities with past successful campaigns. Maybe you take the time to work with your call center employees and teach them about certain behaviors they can perform to reduce churn.

As you roll out your solutions, make sure you understand how you will measure their impact. A sound monitoring system should be in place you so you can promote the aspects of your customer churn reduction plan that are working.


together solving churn

Making BETTER-Informed Business Decisions

As a business leader, you’ve probably heard hundreds of iterations of the phrase “Challenge the status quo.” Management experts and industry leaders have been told to tackle conventional thoughts and systems head-on for as long as they’ve been around. The only issue with this phrase, though? It’s become so common that it’s become the status quo!

It’s all too easy to settle for a technique that works, even if there are better options out there. Companies often rely on antiquated processes because they’re familiar with them. They fail to explore new ways to make better-informed business decisions in the name of comfort. If you’re ready to break away from this norm and make a change, this article is for you.

Reducing Churn With Real-Time Data

Although it’s been a trending topic for some time, there is still a lot of confusion about what big data collection can be used for. Simply put, a collection of extremely large data sets can be analyzed to reveal correlations, trends and patterns. These trends often hold powerful insights, that if acted on quickly, can provide awesome results by way of reducing customer churn, increasing customer satisfaction, and will usually result in an increase in company revenue.

Getting data in real-time has many advantages and possibilities, but it’s gaining traction in the business sector because it allows companies to make better-informed business decisions. Historically, organizations had to look at the past to create business insights. For example, they would gather information from the prior day, month, quarter or year and then create reports, projections and working plans from said information. Today, businesses that want to make strategic moves can rely on real-time analytics to inform action. Instead of looking back, decision makers can visualize current data to make time-relevant decisions when they matter most…now!

In the past, a simple question like “How many customers are about to leave our service?” could take hours or days for teams to understand. More complicated questions often took weeks or months to be analyzed. With real-time data being used, answering complex questions is no longer a burden that takes time. In seconds, you can receive a robust answer to your most complex business queries.

The opportunities of real-time data are endless—as long as you know how to access them. For most companies, this technology seems foreign, complicated and time-consuming. Luckily, this couldn’t be further from the case. With a small amount of know-how, every business— regardless of size—can start to use data to make better business decisions.

Knowing The Customer

Experts suggest that companies first use data to better understand their customers. It seems today, people only stay with a company if they have a very good reason to do so. There’s plenty of competition and similar offerings in almost every market, which makes it very hard to gain loyal customers.

As a result, businesses must work harder than ever before to avoid churn and increase customer success. Real-time data can help you understand exactly why and when your customers jump ship. With this information in mind, you can create a plan that keeps customers coming back time and time again.

6a00e54ee3905b8833019aff835edf970Long gone is the need to select and study small samples of customers to try to guess who will be leaving your business portfolio next month. With real-time data, you can understand virtually every one of your customers at any given time. Can you imagine sending fresh customer feedback to your employees instantaneously so they can improve a customer’s experience in real-time? More importantly, can you picture using this technology to turn a bad customer experience into a positive one?

The Goal? Understanding the Customer

With a clear goal in mind, real-time data improves venerable business models. Without a clear goal in mind, this information can do more harm than good. Companies that fail to define what they want will waste their time and money trying to analyze countless sheets of information. Time and money are two of your most valuable resources, so don’t waste either of them for a second. You must create a goal early on and visit it often if you want to use your data effectively. infographic-the-power-of-a-positive-customer-experience-1-638

One major roadblock for decision makers is understanding the picture that real-time data paints. Typically, businesses organize their findings in various charts and graphs—which can tell different stories depending on how the information is enterprited. Fortunately, there’s a new workaround for this issue. Instead of creating pages of visualizations that showcase findings from Big Data, organizations can use a data visualization tool that does it all for them.

This tool creates easy-to-understand visual representations of data. They are designed in a intuitive way, so everyone in an organization can understand them with little to no training. With the help of these visualizations, companies are able to scale up their entire organization’s ability at once.

Industry experts know it’s important to challenge the status quo. However, many of them fail to use this knowledge to drive action. If you’re ready to take your business to the next level, you need to move away from outdated processes. It’s time to stop relying on antiquated business intelligence procedures and transition from capturing data to making it useful.

Departing from the tools and practices that your business knows might feel uncomfortable at first, but it will be well worth it. By 2020, your customer experience will be more important than any brand differentiator. If you learn how to reduce churn rates and improve your customer experience now, imagine the success you’ll have in the future.


Making Sense of Big Data

Data, in whatever form it takes, is on the forefront of most business plans today. If you are the one responsible of making business decisions based on data, you are going to want to make sure you know how to analyze the information as quickly as possible. Take an e-commerce company for example. Your employees aren’t the only ones contributing to your data. Your customers submit data of their own every time they sign up for your service or purchase a product from you. Overall, the numbers from both sides add up quickly and it often takes a significant amount of effort to analyze. The progression of data creation is exponential, with colossal amounts of data generated every day.

Simply put, Big Data is comprised of extremely large amount of information. This definition is important for business owners to understand, but understanding the scope of Big Data isn’t the be-all or end-all. Business owners need to learn about how Big Data can be analyzed for insights that lead to more strategic business decisions and moves.

Below, you’ll find information that will help you make sense of Big Data. After you finish this article, you’ll understand how data is collected, the types of Big Data and what your business can learn from this this data.

The Collection of Big Data

Data collection methods often differ from organization to organization. Some industries and organizations’ Big Data encompasses information on transactions, while others is comprised of enterprise content. What is more standardized across industries, however, are the steps of data collection.

data collectionThe first step of Big Data collection is gathering information. Some companies use web scraping tools to gather their data, and others rely on their customer resource management tools to capture information. Next, companies need to store the data they collect. Many companies build internal automated processes that allow them to store their data in spreadsheets. Others might take advantage of a storing service that saves the information for them.

The third step is data organization. Even if an organization collects data efficiently, they’re likely to collect extraneous information they don’t need, too. So, every organization needs to sort and clean the information they collect and save. A company will likely also have to reorganize their data after it’s clean, so it’s optimized for further use. Last—but not least—companies need to verify their data. Until companies validate the authenticity of their data, they cannot trust any insights the information produces.

The Types of Big Data

Big Data is made up of a mix of unstructured, structured and multi-structured data. Unstructured data is information that’s not organized or easily interpreted by traditional techniques. A great example of unstructured data is a social media post. In general, standard databases and data models are unable to organize and understand this type of metadata.

structured and unstructured dataStructured data almost always has a defined length and format. Numbers, dates and strings of words are a few examples of structured data. Chances are your company already uses structured data that’s stored in a database to inform your business decisions.

Multi-structured data is derived from interactions between people and machines. One of the best ways to remember multi-structured data is to think of a web browser. As a user works on the browser, a combination of text and visual data is chronicled; the browser will also log structured data, like transactional information, about the user.

Understanding Data Improves Business

The amount of insight businesses can gain from Big Data is somewhat overwhelming. Due to this fact, experts suggest that companies focus on what they want to learn from Big Data, not what they can learn. To take advantage of all that Big Data has to offer, you need to establish a clear plan.

Several prominent companies use Big Data to decrease their expenses, and others use Big Data to improve their internal processes. One of the most popular processes right now is to use Big Data to reduce customer churn.

The Four V’s of Big Data

Industry leaders often use “The Four V’s of Big Data” to frame the Big Data discussion. If you need a quick way to remember what Big Data is and how its massive amounts of data are used, think of the following words—volume, velocity, variety and veracity.

The most obvious characteristic of Big Data is its volume. The amount information taken into consideration for business decisions also grows every year, making volume an essential component of Big Data. With an exponential growth model, Big Data’s velocity must also be addressed. Remember, everything from a text message to a credit card swipe can (and most often is) considered part of the Big Data collection process. As more technological advances become established, Big Data’s velocity will only continue to increase.

Variety is another important characteristic of Big Data. When you think of Big Data’s variety, remember that Big Data is comprised of unstructured, structured and multi-structured data. As discussed in “The Collection of Big Data” section, veracity is another part of understanding Big Data. Without prior data verification, you can’t draw valid insights.

ibm-big-dataThe Bottom Line

To use Big Data as effectively as possible, companies need to understand the ultimate value that Big Data offers their operations. More specifically, businesses leaders need to understand how seemingly countless attributes influence their data collection objects.

Screen-Shot-2015-09-28-at-2.05.01-PMThe high elevation view of Big Data can be overwhelming, but it’s pivotal to business success. Currently, companies that aren’t using Big Data to their advantage are stuck in the past. They’re scrolling through countless spreadsheets and data sources trying to make sense of everything. Then, they’re compiling analysis reports that take either months or years to create. By the time these groups are able to make business decisions, their data is often outdated and irrelevant.

On the other hand, companies that use Big Data are ditching the troubles and limitations of traditional business insight creation. These industry leaders use Big Data’s real-time cycle of analysis to make the most informed business decisions possible when they matter most.

If you want to run your company as efficiently as possible and improve your bottom line accordingly, you need to understand your data.


The Best 5 Salesforce Dashboards Every Sales Manager Needs

Sales dashboards reveal a ton of information in a short amount of time, helping sales teams gauge their current standing and informing their long-term strategy.

Information can be tough to process on its own, though, especially when trying to see bigger connections or anticipate what might come next. But with an organized report and accompanying visuals, these insights pop up immediately, spurring action and preventing overlooked details.

To help your sales teams make the most of their sales data and listen closely to the story it tells, try using one of the following 10 best Salesforce dashboards that can enable success:

Current Deals by Pipeline Stage and Close Date

This dashboard helps you instantly visualize the potential earnings you can obtain from deals while helping you assess how many people you have in your current funnel.

Start with a table column listing each pipeline stage, and then list the total estimated deal value for each stage by expected close date on the corresponding row. The result should be a stacked bar graph that reveals total revenue possibilities arranged by date and color-coded to indicate how many deals are in their respective stage of the pipeline.

 

  • X axis: close dates
  • Y axis: total deal values
  • Data series: listed by conversion stage, arranged as a stacked bar graph

Conversions Over Time

Converting people to the next stage of the pipeline is the key to consistent revenue earnings, helping teams focus on the activities that keep them consistent.

To reveal this information, start with a column of conversion actions — e.g. “second meeting to software demo” — and then list the conversions for each sales period in the corresponding row. The result is a line graph that reveals pipeline movement over time for each stage.

 

  • X axis: sales periods
  • Y axis: total conversions
  • Data series: a separate line graph for each type of conversion

Inbound Leads Over Time

This graph reveals how effective marketing is at bringing in leads to sales reps, reducing the amount of cold-calls and “hard prospecting” needed.

The Salesforce blog provides advice on how to set this one up, but the gist is that you will end up with one simple line graph that tracks total inbound leads over time.

 

  • X axis: sales periods
  • Y axis: total number of inbound leads
  • Data series: just one line graph tracking inbound leads, can be separated into inbound source to determine value of marketing activities

Sales Leaderboard, Earnings Progress Reports

The sales leaderboard can be displayed as a ranking list displayed on a table, but it can also be split up into several types of graphs to track closed-won trends or highlight weaker performers.

 

  • Table: Arranged by top earnings per sales rep
  • Graph: sales rep closed-won deals over time
    • X-axis: sales periods
    • Y-axis: earnings
    • Data series: separate line graph for each rep
  • Graph: total closed-won deal values over time
    • Same as above, but each sales rep is arranged as a stack bar graph rather than separate line graphs

Closed-Lost Reasons

Sometimes focusing on your weakest areas can help you determine where to make the most improvements. You can start by requesting that reps diligently record reasons behind each closed-lost sale, preferably from a simple pick list accompanied by more detailed notes.

Then, the total closed-lost deals can be viewed as a pie chart.

 

  • Pie chart: Reasons for closed-lost deals as a percentage of total
  • Data series: A separate wedge for each closed-lost reason, pie can be broken down further into losses to competitors or losses at certain pipeline stages

Using a Data Visualization Tools to Automate Salesforce Dashboards

If you happened to glance at the Salesforce blog linked to above that instructs you on how to create the “inbound leads over time” dashboard, you will have noticed that the process of turning your data into a graphic representation is fairly complex.

Rather than taking multiple steps each time you want to generate a report, you can use a third-party Salesforce data visualization tool that can generate dashboards in real time and help you keep up with the most important metrics.

By consistently visualizing and interpreting your data, you can stop guessing what you need to do to sell more and start knowing, helping you sell more than ever before.


8 Tips to Manage Your Pipeline Like a Pro in Salesforce

When focusing on just one customer or account, the journey someone takes from initial awareness of a product to a completed, successful sale is crystal clear. Unfortunately, no sales rep on Earth has the luxury of handling just one account at a time. Instead, they are juggling multiple, all at different stages and levels of interest.

It can get confusing, to say the least! Tools like Salesforce can make managing all these people easier, especially when you use the following eight Salesforce pipeline management tips and best practices:

Start With a Well-Defined Process and Pipeline

The vocabulary of your sales pipeline should be ingrained in your reps’ minds. Each one should be familiar with the various stages, and they should know for sure how to identify which stage a lead is in based on activity and indicative factors.

Train your reps on this process, make simple-to-follow logic flowcharts to decide if a client is in a certain stage, and post reminder graphics all over the office so they never have to think twice about it. These efforts will make data entry and reporting in Salesforce much more effective and likely accompanied by a higher adoption rate.

Use a Pick List for Categories When Possible

Manual data entry can get tedious, but coding in a set of clear options for reps to pick from can make data entry go by quicker and encourage more people to actually do what they are supposed to.

Try to limit the amount of categories you have (more on that in a moment), but do ensure that each option is distinct and clear. Depending on the form in question, you may also want to include an “other’ category where the rep can write in their own information.

Include a Secondary Open Form With Picklists

Picklists are fast and generic, so accompanying them with a form where any text can be entered can allow reps to track important details.

Qualify and Categorize Leads

One of the first entry forms to include in your pick lists are lead qualification descriptors. Every incoming lead should have either a business category, interest level, referring source, or all three so that reps have as much information as possible when trying to prioritize activities.

Avoid Too Many Pipeline Stages

In reference to limiting categories as suggested above, the Salesforce blog recommends that you avoid having over four or five discrete phases to your sales pipeline. With too many possibilities, reps can get confused or have different interpretations regarding when a client is at a new stage. The amount of unusual movements that skip stages or move backwards also increases.

So, stick to the K.I.S.S. and make everyone’s life easier.

Use the Calendar and Reminder Features

The worst way to lose a sale is to have a lead effectively die within the pipeline. Ideally, every lost sale will be “closed-lost” rather than “Shoot! I forgot about them!”

To prevent these oversights and to keep everyone flowing along, you can use the internal calendar and reminder features to help automate tasks. For example, someone who receives a demo should be prompted to receive a follow-up email automatically after one or two days. That way, no one gets forgotten.

Make Entry Forms Dependent or Required

Required forms must be completed before submission. Dependent forms must be completed before the next related form is available. Configure both to prevent incomplete entries into the system and to get reps to pay close attention to how they describe a lead or their activities.

The Most Important of Salesforce Pipeline Management Tips: Track Sales Activities

Reporting and monitoring tools can help ensure that reps are doing what they are expected to on a weekly, monthly and quarterly basis. Even though this strategy doesn’t track individual leads, it does approximate the level of activity expected to handle the current new lead volume. I.e., sales reps should be making a certain number of calls every period to keep the pipeline flowing.

You can make tracking activity easier by using a third-party Salesforce visualization tool that can instantly alert you to every rep’s actions. Some tools, like VisualCue, also track each account to make sure they are not forgotten, so if you need a leg up on managing your pipeline, consider using a sales rep monitoring tool today.


The 5 Biggest Problems with Salesforce Reporting and How to Fix Them

Today’s Sales Managers and VPs are facing a lot of frustrations with their current CRM systems. Whether it’s missing information, lacking real insights or inaccurate, duplicated reports, there is plenty of room for improvement in modern Salesforce implementations.

Why all the difficulty? Gene Marks of Forbes writes, “the problem with your CRM system isn’t usually about your CRM system.  It’s about you. It’s the way it’s been setup.  It’s the way it’s been implemented. It’s the way it’s managed. Wake up.”

The good news about this is that if Marks is correct then there is hope: the problems with the modern CRM are user-based and that means they can be fixed with a few simple changes which we will outline below. The technology is in place, all that it requires is putting insight into best practices. We will start off with the five biggest reporting problems Salesforce users face and then provide solutions for each of them.

Missing Information

By missing information we mean specifically missing customer information, whether it be outdated or missing contact information or missing data about the status of an opportunity at the front end, when sales reps input the wrong kind of information into salesforce. With modern calling systems the likelihood of manually inputting an erroneous phone number or email is small.

The more likely scenario is that your CRM is missing data surrounding a customer’s status in the pipeline. If your pipeline is missing this information then your forecasting won’t be as accurate and you will possibly lose opportunities that could help your bottom line.

No Context

The context of your data is how it relates to other sources of information. For example, in Salesforce you can run a report about the number of closed deals this month, won or lost. However, without linking in your marketing data you wouldn’t know where those deals came from, how long they spent in marketing, or what the CAC to LTV ratio is.

This is the sort of information you need to make an informed decision about which marketing sources are giving you the best leads, and the reports you can run in Salesforce simply do not answer this question because data from your other sources simply isn’t blended and analyzed as an integrated whole.

Difficult to find information

If you have solved your missing information and data context problems there is still work to do. Even with these improvements your sales team is likely still struggling to find the information they need exactly when they need it. This on-demand data analysis and recall is an incredibly valuable tool, and is too often missed due to poor data management. Poor data management occurs when your sales representatives do not know how to extract and analyze the data they need because the system is too complicated.

This is an especially difficult pain point for sales managers because of the time wasted in trying to find information on a prospect’s history at a crucial juncture in the sales call or customer service ticket which often leads to frustrated sales teams, dissatisfied customers and wasted opportunities. By putting all the information about a customer right at your team’s fingertips they could more efficiently manage their time, be more productive and close more deals.

Insufficient Reporting

There is almost no end to the different types of reports you can generate in Salesforce. Because the tool both collects the data and generates the reports you can blend different data points (the kind that Salesforce collects) if you know how to navigate the system. The problem is that many sales reps do not know which reports they should be generating and how to generate them.

The difficulty with this insufficient reporting is that sales managers will often have dozens of reports on their desk coming in from sales reps with no idea of how they all connect together, how up-to-date they are and whether or not tracking this report is going to do anything to positively affect their monthly targets.

The solution to this is a data visualization tool that can generate the reports you need and immediately deliver them to your inbox when the data changes. The Data Visualization tool essentially takes the data that Salesforce is generating and allows you to visualize it in such a way that makes the actionable intelligence more easily understood. When you pair these visualizations with real-time alerts you get the most value out of your Salesforce data because you can see and understand what needs to be done in the moment.

Duplicate Reports

Once you know which reports you should be generating there is one last problem that many managers complain of when it comes to Salesforce reporting: these reports are half-baked, inaccurate, or duplicates. The data makes sense but cannot be correlated to improving Sales. You will likely see the same data points circulated around different reports to the point where you know one metric backwards and forwards but still aren’t seeing any improvement in your bottom line.

The Solutions

The answer to each of these problems can be found in add-ons to Salesforce that both visualize data from various sources and present it in a simple way that allows you to take action right away. You can even get started with a free version of VisualCue, a data visualization add-on focusing on eliminating the need for complicated reports.

 

Problem 1 – Missing Information

 

  • Use an auto-dialer, an email system that integrates directly with Salesforce such as Telephony or RingDNA.
  • To avoid missing status updates ensure that each of your sales representatives is trained on how to pass information to their sales manager quickly and clearly.

Problem 2 – No Context

  • Use a data blending tool like Pentaho or Hadoop to integrate all of your sources into one data visualization and analysis tool so you can visually make connections between sales and marketing or sales and customer service data.
  • Choose a sales performance platform with the ability to connect to different data sources and then visualize all of that data together in one tool. These tools include VisualCue, ClicData, and Zoomdata.

Problem 3 – Difficult to Find Information

  • Conduct a brief survey of your sales team and discover which data points they most often need when they are preparing a presentation. These are going to be the main points in your customized dashboard.
  • Invest in a sales performance platform and data visualization tool that both allows for customized dashboards and visualizes the information your sales reps need in an intuitive and understandable way. These tools include Zoho Reports, VisualCue and Microsoft Power BI.

Problem 4 – Insufficient Reporting

Track information in the following 5 reports below with a program like Necto or ClicData that delivers updates to your inbox when the data falls below a performance threshold. Performance thresholds should be specific to every organization.  While these are not the only reports you should be tracking, it is a great start to make sure that your organization is headed in the right direction.

Top 5 Performance Thresholds

 

  • Lead Response Time
  • Activity Efficiency Ratios
  • Top 10 salespeople by step
  • Open opportunities by stage and time
  • Time spent in each stage

Problem 5 – Duplicate Reports

Set up the five thresholds we listed above sent directly to your inbox. Then, use your data visualization tool to include a second list of “tangential” issues that aren’t crucial to your day to day but are valuable for understanding the bigger picture. This way you won’t have duplicate reports cluttering your inbox.

These 5 issues with Salesforce reporting certainly can be a pain for the modern sales manager or Executive, but that is no reason to think that your CRM isn’t doing its job. You simply need to reevaluate your reporting strategies and you will soon find your entire sales department operating more efficiently.