Categories: ABM, Artificial Intelligence, Customer Data Platform, Discovery, Marketing, Predictive, Scoring,
It’s 2020 — are you excited about building your next target accounts list?
It’s true you want to expand your current list of accounts, but you’re likely not looking forward to going through the slow, manual process of finding and handpicking who to target.
Unfortunately, this is the sad truth for too many B2B companies, but this year doesn’t have to be the same for your company.
What if there’s a way to overcome the overwhelmingly tedious task of building target account lists?
You already have a handful of accounts you want to duplicate, which is more than enough to develop look-alike models. All you need now is an AI-powered customer data platform to handle the rest.
The Growing (and Expensive) Problem in ABM Marketing
Account-based marketing continues to be an effective B2B marketing strategy. Yet, there’s a growing problem that’s turning this method into an expensive and time-consuming ordeal: cloning your best customers.
Does this sound like your company?
Your business did well in 2019, and now you’re looking to scale ahead. So you have your sights set on growing your list of accounts. However, you’re faced with the issue of finding accounts to target. It’s difficult to know where to start and which named accounts to add to your “hit list.” The depth of the web is far and wide, making it cumbersome to conduct your search manually. So instead, you purchase a lead list from a vendor. Not a bad idea, right?
After all, you’re saving yourself time by quickly generating a starter list of leads. But as you’ll quickly learn, this is can turn into a nightmare.
Why Buying Lead Lists from Vendors Isn’t the Answer
At first glance, it seems that purchasing lead lists is the answer to hastening the process of creating a named accounts list. However, as you begin poring over the data, you’ll see things like:
- Inaccurate data (outdated information)
- Duplicate data (accounts you already have)
- No way to identify qualified leads
Having a list of 1,000 leads doesn’t mean you have 1,000 potential accounts. The lead lists vendors supply use shallow data, containing the typical firmographic information (company size, revenue, industry).
So not only do you have to scrape away all of the outdated and duplicate data on the list, but you also have to go through your best customer accounts and pinpoint which of the leads on the list match your ideal customers.
Now, you’re out X amount of dollars you spent for a useless list of leads, and you have to spend countless man-hours picking through the weeds anyway.
That’s not how you want to spend the first quarter of 2020, nor should you have to.
How Look-Alike Modeling Enhances B2B Marketing Campaigns
Your goal for 2020 is to increase your revenue, which means you need to focus on attracting more of the right accounts to your business. You can achieve this using look-alike modeling technology.
Leadspace’s customer data platform automates the process of finding the most qualified net-new accounts based on your best existing customers.
It does this using deep learning AI, which will analyze the best accounts you hand select from your database. The good news is that you don’t need a long list of accounts for the CDP to learn. A small sample of accounts is all that’s needed.
The platform will use a combination of machine learning and comprehensive data enrichment. It uses a mix of 1st and 3rd-party data from any number of sources.
The goal is to identify firmographic and person-level data, such as department size, job titles, roles, specialties, technologies used, and expertise.
This will ensure you have a target list of qualified accounts that match exactly what you’re looking for in a good customer. Plus, your sales and marketing teams will know who to reach out to when the time comes.
You have the option of determining how wide or narrow the CDP casts its web.
Now, the concept of having a fully automated process for generating a list of highly-qualified targets may sound too good to be true, but there are already businesses reaping the benefits of adopting the Leadspace CDP for selecting target accounts.
One company was able to increase its conversion rates by 20% and its target market reach by 13%. So not only did they get more of the same accounts, but they were also able to break into markets they never thought to tackle.
It’s Time to Reap the Same Benefits in 2020
With Leadspace, you can empower your B2B marketing team to find net-new accounts that closely resemble your best customers (even those in other markets).
You’ll be able to predict which accounts are highly likely to buy, and you can score accounts based on other criteria, such as who’s likely to stay long-term, who’s easy to upsell to, and so on.
Imagine the possibilities with your ABM strategy!
Now, you don’t have to just imagine. You can explore our customer data platform today.
But before you do, take a look a look at our 4-Step Scoring Program for ABM Success so you can ensure the best results.