There is an old Zig Ziglar quote that says: “The top salesperson in the organization probably missed more sales than 90% of the sales people on the team, but they also made more calls than the others made.” As motivational as this can be, it sounds more like something a sales rep would say to get out from administrative work, such as adding data to your CRM system.
Arguably a sentiment shared by a lot of sales professionals, it is best articulated in a comment to CBS News Geoffrey James’ question regarding the sales process. BNET member “dawngio” wrote:
“I agree that customer information needs to be accessible and kept up to date for the benefit of both sides. On the downside however, sometimes a company will institute what is euphemistically being called a ‘Sales Process’ comprised mostly of some expensive CRM software… to ‘make the sales process more efficient’ which, in my experience, only leads to two things….
“1. It sets up an environment of Big Brother micromanagement. Reps (especially good ones) HATE to be micromanaged. Will it weed out the ones who are not making the minimum or quality calls? Yes, but it will also tick off the best reps and decrease their productivity managing minutiae instead of doing what they do best, which is SELL.
“2. It is not likely to provide Management with the data for analysis that they were hopeful of when purchasing the magic CRM system – Garbage in, Garbage Out – the reps will input what management wants to hear whether it is reality or not. (Sorry, CRM Sales Reps, but I’ve been doing this for a ‘lotta years).”
The article and comment came out in 2008. And, while a lot has happened in CRM technology’s decade, attitudes and sentiments don’t always follow.
The State of Sales Productivity
In 2015, Docurated conducted a survey among 127 marketing and sales executives regarding sales productivity.
It found that many believe their reps to spend only up to a third of their time doing actual sales. The rest is spent looking up or creating usable content (31 percent) and administrative work, such as updating the CRM system and reporting (20 percent).
Despite these findings, many of these executives still hold sales productivity as the top driver for reaching new revenue targets (79 percent). And, they are actually investing in tools that are supposed to improve this. Companies typically spend around $24,000 per person, in bids for better productivity. A gap lies in investing in tools that actually measure their progress, with 49 percent of respondents having zero to limited productivity measuring capabilities.
Where Does This Leave CRM?
All this puts CRM in limbo.
On one hand, your CRM system is central to your sales operations. It is a technology that has matured through the past decade, and is no longer a glorified rolodex. This is true across CRM products, from enterprise-scale to even lower end options.
With CRM, you get a gamut of advanced features, such as opportunity and contact management, integration with third party applications, and comprehensive communications across different channels, such as email and social media. When it comes to improving sales productivity, it is one of your crucial tools.
However, on the other hand, it is still an investment from which a good number of companies fail to get a return. In the worst cases, some have even lost money on their CRM system, which can run up to $8.2 million per year. Studies point to ‘bad data’ as the cause.
How Do You Solve a Problem like Bad Data
“Garbage data in, garbage results out. Whether you do inbound or outbound marketing, the quality of your database and lists has a huge impact on your results.” – MECLABS Executive Director Brian Carroll
Experian, a business services company, conducted a 2013 survey of multinational companies and found that 91 percent were beset by data errors. These errors include incomplete, inaccurate and duplicate data.
Within a small sector of a company, such data errors may seem negligible – something you can just ignore. However, when this data travels through a multinational company’s massive hierarchy, its damage becomes massive, as well.
Remember too that bad data is one of the top contributors to your sales team’s performance. It could lead to missed opportunities and inefficient sales processes. It could also be the observed trade-off. After all, your CRM system is a good thing. But, it remains a tool that you need to use properly if you want to reap its benefits.
The Costs of Bad Data
There are several possible causes of bad data. This includes:
- Human error
- Faulty communication among stakeholders
- Faulty management strategies
- Lack of relevant data
If you are to make the most of your CRM system investment and improve sales productivity, alleviating these causes is crucial.
Flawed business intelligence: Forecasting and reporting using bad data will skew the results. Your executives then have to base decisions on flawed intelligence reports, which defeats the point of having these reports in the first place.
Faulty sales and marketing automation: A lot of the automated work – such as follow-ups and marketing campaigns – depends on having a reliable database of contacts. With bad data, you end up using your automation and sending content to wrong format email addresses and the like.
Increased frontline errors: Your customers might also witness bad data-driven errors, such as wrong product pricing, wrong customer information and faulty loyalty incentive programs. This is a turn-off, at the very least. You might also end up losing customers.
Wasted opportunities and time: 77 percent of the respondent companies in the Experian survey claim to have fallen short of their targets because of inaccurate data. They missed opportunities, and underperformed in sales and other aspects of their operations. In the long run, they miss out on the expected returns from their CRM investment.
Fixing Bad Data
The first step to fixing bad data problems is to keep yourself from putting blame on anyone in particular. Bad data is an organizational fault, so responsibility is not just on one person or team. In the same way, addressing bad data is an organizational responsibility too. Here are a few basic steps to take:
Address errors generated by your team within your team: It is important to take ownership of errors generated by your team. Acknowledge your responsibility and then implement controls that minimize future errors and track compliance. Team members need to be trained on data entry best practices and acceptable standards.
Implement strong organization leadership when it comes to data quality: The initiative towards good data and data integrity should be top-down. It is not just about key executives lending support to initiatives that fix bad data and implement reforms. There should be a recognized leader. Traditionally, this has been the role of the Chief Information Officer. However, of late, appointing middle management as data officers is also being done. The appointed head of data quality should lead by example, demonstrating best practices and implementing monitors that ensure compliance.
Make the most of built-in data control automations: Many of today’s CRM systems include the ability to customize data entry rules and standards. You can define required fields, auto-population rules, field dependency rules and more. Likewise, make sure to implement acceptable parameters when it comes to web-to-lead data. Limit data entry/editing access to authorized personnel only.
Implement an organization-wide quality control process: The first step here is to pinpoint your CRM system’s entry points and utilize data cleansing tools at these points. This ensures rich information as the data enters the system. To date, around 23 percent of businesses still opt for manual data checking, which exposes organizations to more errors.
Then, schedule batch data cleanses that check for duplicates, obsolete data and the like. There are applications that can automatically do this, such as UnDupe.
The initial process that you implement might not the best for you so consistently monitor for data integrity. Tweak your process where necessary.
Big Data: the Next Frontier in Productivity
A study by the IDG points to an investment of $8 million on big data by 2014. It also claims that about 70 percent of enterprise companies and big organizations are ready to or have plans of engaging in big data initiatives.
Today, we know that big data is big. It helps executives make data-driven decisions. When integrated with your CRM system, it can predict the behavior and needs of your customers, and improve customer engagements.
We also know that this starts with the good data that you can guarantee today.
What Exactly is Big Data?
Big data has taken on a catchall status, and is used to describe the massive volume of data, made possible in today’s information age. In business however, it more specifically refers to the storage and processing of large amounts of transaction and analytic data, in both structured and unstructured formats.
The goal, of course, is to help businesses become more data-driven, efficient and effective, relying on accumulated information at all operational levels. An impediment here, on top of security, privacy and complexity, is bad data.
The Value of Big Data
There is great value in the move to acquire and use big data for businesses. For one thing, you can be accurate to the very detailed level on all aspects of your operation, including customer engagement and product inventories. You can then be more responsive and make better real-time decisions. You are also able to see a more accurate customer segmentation, which allows you to develop products and services that they really want.
Big Data and Your CRM
Your CRM system and big data go together, especially since this is the system that processes some of the most crucial information within your operations.
When you integrate big data with your CRM, you get access to new tools that allow you to identify new marketing and sales opportunities, integrate internal data with external transactional data (such as those from your social media presence and websites), and better manage your customer engagements.
Here are some benefits from integrating big data with your CRM system:
Improved customer-centric operations – With big data, you get a clearer picture of the performance of teams that directly engage with customers, such as marketing, sales and customer support. Using these performance metrics, you can implement adjustments where necessary. You can accurately predict the returns from these improved engagements and invest more where there is greater returns.
Benchmarking – Through more accurate metrics, you can implement benchmarks that become operational standards within your organization. These benchmarks are based on key indicators, such as customer retention, and cost vs. revenue. Through benchmarking, you can focus on the aspects of your operation that needs improvement.
Better customer knowledge – Through big data and CRM, you can know your customers better since you get your analyses from across all customer touch points, such as inbound calls, social media, websites and email. You can map trends that help you predict customer behavior and needs, and develop content, products and marketing campaigns that are responsive to these behaviors and needs.
Improved decision making – As long as you have a customer-centric/ customer-facing operation in place through CRM and big data, you can make better decisions.
Predictive modeling – One of the key advantages of big data is that it gives you the ability to accurately model customer behavior. Through demographics, engagement and behavior histories, and other accumulated data, you can develop a model of your ideal customer and accurately predict their future behaviors and needs.
So, Is There a Trade-off Between Good Data and Productivity?
The top names in CRM have begun their investment in big data. This includes Oracle, Salesforce and Microsoft. They’re hard at work at developing the capacities and technologies that are capable of processing massive amounts of data.
According to a Gartner-led research, there is currently a glut in unstructured and unprocessed data. This is set to increase by 800 percent come 2020. This represents a challenge, yes – but also, potential for improving a company’s bottom line.
Big data, good data, data… when used optimally and intelligently increases your overall productivity. There’s no need to wait for big data technology to mature. You can already see this in model organizations that have learned to engage their employees in complying with strict data standards and best practices, and are able to use the results in becoming more efficient, effective and profitable.
This article is originally published at Tenfold.
