Sales and marketing are constantly evolving and adapting to new techniques and approaches. What worked five years ago has now been left in the dust. Keeping ahead of your competition has given rise to the importance of RevOps.
Responsibilities on RevOps have increased – from breaking down silos between sales, marketing, and customer success to lead scoring and identifying the most vital strategies. As a result, RevOps are shifting the focus to data orchestration tools for efficiency and accountability, ultimately driving revenue growth across all teams.
This ultimate guide helps RevOps plan the rest of the year. The guide covers:
- Major Challenges for RevOps
- The Shifting Focus to Data Quality
- Why Data Orchestration is Crucial
- Difference Between Data Orchestration and Integration
- The Right Type of Data You Need
- Why SalesIntel is a Reliable Data Partner for RevOps
Major Challenges for RevOps
RevOps is a powerful way to drive more revenue through your business. Still, as a relatively new operational concept, there are a few potential RevOps challenges you need to keep in mind:
Revops can end up supporting every lead with little focus or direction. Trying to impact every possible prospect leads to situations such as:
1) Poor lead to opportunity conversion rates for marketing or sales teams
2) Slower lead to opportunity conversion timelines
3) Cost overruns for MAP and CRM systems that are often priced based on database size and API calls
4) Friction and poor performance across the GTM team due to a lack of alignment
When marketing and sales work all leads equally – inevitably, conversion rates suffer because the team spends time on low-quality accounts and contacts at the expense of high-quality accounts and contacts.
With data-backed prioritization, the best leads in the company get routed and worked quickly.
Prioritization requires an understanding of your ideal client profile (ICP). Without a clear definition of ICP, sales-marketing alignment breaks down. Leadership and team members anecdotally and qualitatively debate “quality” instead of knowing the definition and working together.
Every aspect of business and every department will have its challenges. However, all these challenges for RevOps point to using the right, relevant, and accurate B2B data for revenue generation activities. The right data will help you identify your ICP and find more high-priority accounts to target.
The Shifting Paradigm From Data Quantity to Data Quality
Earlier, sales reps and leaders followed a simple thought process – the more data, the better. Data quantity was considered at the top of the checklist when choosing data.
Revenue Operations (RevOps) teams are focused on the alignment of sales, marketing, and customer success operations to drive growth and keep all teams accountable to revenue. To do this, they need quality data.
According to Experian’s Global Data Management Research, only 51% of teams consider the current state of their CRM data to be clean, accurate, and useful.
To enhance operational efficiency, RevOps teams need data quality tools to cleanse, normalize and unify their B2B data into a complete and consistent data set accessible to all parties.
Teams looking to purchase data should search for a source that can supply accurate, up-to-date, and dependable data across the business and assist in managing it in real time. This is where data orchestration is the next focus for RevOps leaders.
Why Should Companies Focus on Data Orchestration?
Data changes and decays over time. Every time someone changes jobs, switches phones, or moves, their data changes, and your current database becomes inaccurate. If you’re not regularly double-checking and updating your data, then annual data decay compounds. On average, only 50% of records in any given database are correct.
According to Alluxio, major developments in data technology occur every 3 to 8 years. That implies a 21-year-old firm may have used up to seven distinct data management systems since its beginning, transferring and scattering data over several separate platforms. Your options are keeping your data spread across all those platforms or catching up with orchestration. Not to mention unique systems used by sales, marketing, and customer success.
Executives are turning to data orchestration tools to combat this pace of data disorganization.
Data orchestration is collecting and organizing siloed data from numerous data storage places and making it available to data analysis tools. Businesses can use data orchestration to automate and expedite data-driven decision-making.
A well-planned data solution enables you to enhance, cleanse, and unify information for organizations and contacts, develop insights, route data where needed, and maintain high quality, coverage, and compliance. Good data management frees teams to focus on high-value, strategic projects and prospecting by automating tedious data-related chores. No more sales reps wasting time updating the same contact in three different systems and marketing messing with multiple CSV files to put an email list together.
The 3 Steps of Data Orchestration
The orchestration process is done in three steps:
Your data orchestration technologies must first comprehend and arrange both current and incoming data. Your organization may have data in legacy systems, cloud-based tools, data warehouses, or team-limited tools. Data orchestration technologies must be able to access that data wherever it is and understand what sort of data exists and where it originated from.
Data orchestration solutions collect data in many formats and turn it into a single standard format. Because you won’t have to spend time manually reconciling data, data analysis will be faster.
A basic date may be acquired in various ways. One system may gather and save the date as January 21, 2023. Another system could gather it and save it in the numerical format 01212023. Because of this difference, data analysis might take time and effort. By standardizing everything, you can search and use all the data available.
The most crucial orchestration aspect is making data available to the appropriate tools. This is known as activation. Activation occurs when orchestration tools provide data to the tools that your company utilizes daily. As a result, when you need data, it is already there – no data loading is necessary.
Not only do all three phases occur concurrently, which speeds up data analysis, but they also occur in real time. Real-time orchestration allows you to examine data that has just been acquired.
Is Data Integration and Data Orchestration the Same?
No, both are two different processes.
So, what is the Difference Between Data Integration and Data Orchestration?
Data integration is the process of centralizing data automatically to give a single source of information. This improves data accessibility for teams and systems that require it, such as a data orchestration system. Data integration entails linking various data sets. It collects data from several apps, the cloud, or third-party sources and keeps it in a centralized area, like a data warehouse.
Data orchestration is the coordinated, automated process of cleaning, enriching, and routing data based on customizable rules and processes. It organizes and prepares data to extract value. Data orchestration is the multi-step process that prepares data for more effective GTM execution. It ensures data is error-free, appropriately structured, and mapped to the correct fields in each platform.
Types Of Data You Need to Boost Revenue Generation
A good B2B communication database is the foundation of every effective marketing and sales strategy. No matter your company size, a complete and organized source of truth is critical to have accurate information on your prospects and leads.
The more you understand your prospective customers, the more efficiently you can market to them, develop products and services that match their needs, gain strategic insight, proactively recognize buying intent trends and boost your chances of success.
Choosing the right B2B data provider will have a direct influence on the effectiveness of your marketing and sales strategy. To ensure a more focused approach to your marketing activities and a targeted sales message to your prospects and leads, the B2B data types listed below should be in your database.
Firmographic data contains crucial organizational facts such as business size, revenue, and location that assist you in categorizing accounts (companies) that are appropriate for you.
Think of the contact information as the enabler that allows you to contact the people behind the accounts. These are your mobile phone numbers, email addresses, and job titles.
Technographic data includes information on the technologies employed by the target accounts/companies. You’ll learn if a company is using a competitor already or if they would require specific integrations.
Intent data analyzes the purchasing intentions of people in your target accounts. By tracking web traffic and activity across a company, you can learn when they are likely in the market for a solution or dealing with a specific problem.
The data sets listed above are essential for accelerating the sales process and closing more B2B deals.
You can learn more about each data set and its relevance. Given this, you must also guarantee that the data you utilize is correct and up to date.
How SalesIntel Can Help RevOps Solve Their Challenges
Everything you need to identify your Ideal Customer Profile
SalesIntel has everything you need to help identify your ideal customer accounts (ICP) and build a quantifiable definition of a quality lead, including:
- 22M accounts under management
- 12,000 buying intent signals from Bombora
- 100M B2B contacts with titles and company name data points describing them
By combining our B2B data with your closed internal won, lost, renewed, churned, and expanded account data, we identify your ICP and define it in quantifiable data terms. As leads come in, there is a scalable, automated way to check the lead against this definition and determine its quality. High-quality leads will immediately be available for contact by sales and marketing.
SalesIntel helps RevOps take a scientific approach than trial and error
Once you deploy your ICP and lead definition internally, RevOps can support operations, reporting, and analysis that drive marketing and sales teams toward highly effective lead generation and conversion. Planning, alignment, data, and analysis replace hope as a strategy and replace it with a scientific approach to building the pipeline.
RevOps needs to know where to focus. SalesIntel helps companies reduce the overall data load managed across Marketing Automation and CRM systems, as SalesIntel users can focus on defining and refining ICP and prioritizing perfect-fit leads. A constant flow of ICP accounts keeps the GTM team efficient and materially reduces Revops costs.