SalesFitRx BLOG

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Big_Data_2_-_333_shadowForget about yesterday’s estimates and gut-feelings – today’s knowledge-driven economy requires a data-driven approach to improving your sales processes and performance.

The pressure is on for sales teams to follow the lead of customer service, finance, and marketing departments, by collecting and applying the metrics and data they need to optimize performance.

What Are We Shooting For?
The goal is to gather, organize, and apply the data you need to determine how your team can work smarter – not harder. But this also requires overcoming the ingrained tendencies of your sales team, and encouraging them to utilize the tools and technology they need to provide accurate and up-to-date metrics.

Gone are the days in which new sales reps are added to help meet increasing quotas – today’s C-suite wants to see their projected ROI before adding new staff, and a focus on increasing the efforts and productivity of current sales reps is far more cost-effective.

To outperform their sales quotas, today’s sales leaders must address the challenges of business – and big data can help.

Today’s Sales Technology Landscape
The introduction of new technologies (such as cloud-based data analytics, and integrative sales management systems) creates a real opportunity to address sales productivity and increase performance visibility by streamlining the collection of sales information, and consolidating your important data into one common location.

These systems provide complete visibility – meaning your accurate, up-to-the-minute sales info is accessible to sales reps and leaders from any location (even while on the go).

This transparency and flexibility enables sales team leaders and managers to leverage big data when developing their sales strategies, or assessing current territory assignments and compensation.

It also enables them to monitor current performance, in order to determine which sales reps are on target to meet their goals, and which may require additional training or support.

Additionally, it facilitates the effective assignment and application of resources, allowing team leaders to optimize their approach to meet shifts in the market, or adapt to changing organizational goals.

Leveraging Sales Data
Still, it’s not just about acting in the moment – by assessing historical data, sales leaders can gain visibility into their sales team’s overall performance – not just to assess how and where employees are expending their energy, but to view the effectiveness of their strategy and efforts, over time.

A close look at historical data can help pinpoint organizational issues which may affect turnover or team performance, such as ineffective territory assignments, or other disparities. It can also provide insight into customer behavior, allowing sales teams to determine which clients are most likely to invest in new products and services, in order to focus their efforts on the strongest prospects.

By applying sophisticated analytics to this wealth of consolidated sales data, sales leaders and managers can also predict the future – creating projections which can help clarify where their energy and resources are best spent.

They can also test compensation scenarios, create informed estimates of income and revenue, and develop the strong, data-based strategic approaches which help ensure future success.

Effective Technology Requires Human Leadership
Technology is only one piece of the puzzle. The best sales system is one which is championed by your sales staff and leadership – and overcoming the resistance to change is sometimes difficult.

The most effective approach to onboarding your sales team is simple – show them the money.

Demonstrate how their decision to embrace this new technology will help them streamline their efforts and achieve greater sales success, and you’ll find yourself with a team fiercely devoted to big data.

Let’s Close the Deal!
To learn more about how SalesFitRx can help you leverage your sales data to discover more selling time, increase sales effectiveness, and grow your bottom line – contact me today: | 602-427-2399

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Drowning_330_shadowThe same data that can increase your sales can also bottleneck your sales progress if not handled wisely.

Are you feeling a bit overwhelmed, at times, with the vast amounts of data available? Perhaps you’ve resisted using the tools at your disposal because you didn’t want to take time out to learn how to use them.

Perhaps you simply don’t believe sales analytics will help you land more sales.

If so, you’re not alone. You have an industry full of many others feeling the same way.

Author, speaker and referral sales authority Joanne Black (@ReferralSales) recently wrote a post for the Sales 2.0 Blog about sales analytics called, Are Analytics for Sales a Technology Overkill?

[It’s a perfect companion piece to my post from last week, “Do You Know About This Deadly Trend In Sales Management?” where I featured Jason Jordan‘s resource on the @Salesforce Blog.]

Black opens the post writing about the struggle we have in common with non-selling time:

Oh, how I hate paperwork. Most salespeople feel the same way. We just want to spend time with our clients and close deals. It has been tough enough for organizations to get salespeople to use CRM and provide data. Now sales teams are also being asked to review data and trust analytics.

To be sure, more data isn’t a bad thing, but without solid guidance on how to both effectively and efficiently make the most of that data (i.e. application to your daily sales work), you’ll quickly find yourself lost in non-selling time neck deep in a swamp of data overload.

In the post, Black sat down with Mike Moorman, Managing Principal at ZS Associates (@ZSAssociates), to learn from someone who knows a thing or two about sales analytics and how to use that data to your advantage.

In the past, the sales data available to us has been about past events. But today, we’re experiencing the genesis of an entirely new type of data, and its seemingly endless possibilities, in predictive and prescriptive analytics.

Black’s discussion with Moorman helps us see how this information can assist us in answering questions such as:

  • What’s the optimal size of my sales force?
  • What’s the best way to deploy my people?
  • What are the optimal territories for us to target?
  • What are the best accounts to target?
  • What is each prospect’s propensity to buy?

But even more, we can apply this new level of understanding further into our sales weeks:

This doesn’t just help sales leaders make optimal decisions. It also enables individual sales reps to optimize their performance by answering such questions as:

  • Which accounts should I call on first?
  • What are my priorities?
  • What is my message or value proposition with a specific account?
  • Should I engage face to face or on other channels?
  • What should I send to each unique buyer – an email, research report, video?

Moorman then recommends three steps to get your sales team started on the analytics journey. You’ll definitely want to read those and consider how and when you’ll begin to press these steps into action for your sales organization. Read it all in Black’s useful post.

You don’t need to fear change in the form of a potential tidal wave of data you’ll be expected to analyze, interpret and set into motion. Understand how to use the tools at your disposal, learn to filter what really matters for you and your sales team, and then show your colleagues how to do it too.

A handful of sales reps in your team are going to step-up and lead the rest of you in this way. Make sure you’re one of them.

[Reading Time of Black’s Post: 2:30]

QUESTION: What’s your biggest struggle or frustration with the sales data you can currently access? Is the learning curve too steep with the tools you could use to make sense of the data?

Let’s talk about it…

Click here to download our free guide:
2015 Guide to Sales Optimization: Restoring Sanity to Sales

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Big_Data_312_shadowYour big data, that nearly everyone is holding up like a golden calf these days, is completely useless unless it’s interpreted correctly.

Your organization has data, and it has information. Many of you use the terms almost interchangeably. All the talk from industry pundits…well, in nearly any industry…is that Big Data is going to save the day.

It’s now become something where I [sometimes] listen while picturing infomercial pitchmen plying their wares: “It SLICES! It DICES! It’s also a tasty DESSERT TOPPING!!”

To be sure, there are a lot of knowledgeable people teaching us some very helpful, useful things about big data. But, it’s been lost on many sales organizations the data is useless unless it’s used. By “used,” I mean the data is correctly interpreted and correctly applied for the benefit of your clients and your business.

Data even becomes destructive when it’s misinterpreted because in that scenario, none of the members of your sales team are aware your information is wrong.

The big foundational question you should be asking in today’s environment of instant access to oodles of data is this:

“What is the difference between data and information?”

This is, as they say, your lucky day. I say that because CEO, data quality improvement evangelist [and skiing enthusiast?] Martin Doyle (@DQMartinDoyle for @DQ_Global) wrote a post earlier this year titled, “What Is the Difference Between Data and Information?

Note: This post has nearly 27,000 views since February, so your competitors have learned from this post. [Don’t get left behind.]

In the post, Doyle answers this vital question quite clearly. His background is steeped in data. He’s the CEO and founder at DQ Global (the “DQ” stands for Data Quality), which has been running for nearly 20 years.

The post begins by defining “Data” so we’re all on the same page. In short, he explains that “Data is the 1s and 0s that fill hard drives, and it’s designed to be read by computers–not humans.”

The next section is something I found to be informative. It describes the properties of data in 8 bullet points. Here are 4 that caught my attention:

  • Data is, when clean, a fact.
  • Data can be misrepresented, depending on its interpretation.
  • Data does not mature, nor does it improve with age — in fact, data decays.
  • Data has no value until it is used.

“All data has to be interpreted to be useful to humans…”

Doyle explains that “we can use practically any meaningful unit” of measurement to understand data. The key is that information has context:

“We can see that information has context. It gives us a fact relative to something else.
It offers a yardstick for our decision making.
It lets us derive some kind of conclusion once we understand it.”

After defining information further through a half dozen bullet points, we then move into the meat and potatoes section of the post. It’s explained so well you’ll want to show this post to a colleague. Really.

Moore uses the DIKW Pyramid as a parallel to the process they followed in their process of deduction. Of course the pyramid describes how data moves from information to knowledge to wisdom. His examples are spot-on and they clearly show what he intends to convey.

The author wraps up the post with a section that pulls it all together under the header of, “Better Data – Better Business.” The kicker is a sobering reminder for all of us:

“Poor data leads to the loss of our competitive advantage.”

Yes big data is great to have, but you need to know how to use it correctly. It’s time to read the post and take the next step in becoming the leader among your peers in this area of your business.

If you sometimes feel as if you’re drowning in data, I highly recommend reading this recent post of mine.

QUESTION: Can you confidently say you have a strong handle on correctly interpreting your organization’s data? If not, what do you believe is the next step you need to take? Why haven’t you taken it yet?

Let’s talk about it…

Click here to download our free guide:
2015 Guide to Sales Optimization: Restoring Sanity to Sales

Read more »