(Picture is from www.driftrock.com who helps you grow through Facebook. Advanced targeting, automation and ad management to give you an unfair advantage.)
When it comes to leads, more is not better unless the leads are of acceptable quality.
Much of the MarTech industry is rightly obsessed with what is already in your funnel. Infer, for example will help you prioritize the leads you have in your funnel so you can focus your marketing budget on highest quality leads. This type of technology is terrific, getting better, and will soon be table stakes for all marketers. However, there are at least three good reasons to think beyond this technology. It is likely that...
- There are many companies who are a great fit for your product who are NOT YET in your funnel
- Your funnel may *ahem* not have the cleanest data in the world
- Your marketing budget may not yet be large enough to afford funnel optimization technology
Funnel optimization technologies generally do little to clean data in your funnel or add more high quality leads to your funnel. Tom Tunguz presents a concise view about why you should consider spending resources on improving what goes into the very top of the funnel in his article Sales Funnel Optimization For SaaS Startups. Although this article is written with startups in mind, it applies to many different types of companies. The key takeaway is as follows, "...investing in improvements at the top of the sales funnel, particularly in early prospect and lead qualification are so valuable: they save the time and energy...and can meaningfully improve unit economics."
So we have established that you might want to think about improving your lead quality in 2016. What are your options for doing this? There are at least 4 types of leads providers in today's marketplace.
- Lead brokers: Top of funnel leads. Examples: List Finder, Brokers Data. They will take a look at your company's offering and curate a set of lists that they recommend you buy. Pros: Some are experienced and may have valuable insights. Cons: Lack data sophistication and may take time, energy and testing to find a good broker.
- Commodity lead providers: Top of funnel leads. Examples: Data.com, Dun & Bradstreet. They maintain the full universe of company leads and either provide you a flat file, API, or login access to slice and dice based on what you think are the best customers. Pros: Fairly comprehensive company databases. Cons: No data driven methods to optimize audience and their contact data is middling.
- Call centers. Bottom of funnel leads. Examples: SalesFish, Harte Hanks. These companies will pull leads that they suspect are of good quality and then call all of them and provide you the few that match your minimum sales qualification criteria. They charge by the hour or lead or both. Pros: Much less work for you. Cons: Often expensive and performance varies wildly.
- Artificial intelligence data engines. Top of funnel leads. Examples: LeadCrunch, Radius Intelligence. Use your existing customers to generate a monthly stream of high precision leads that statistically have the greatest probability of closing. Pros: Leverage top data sources and all modern technologies such as data science, machine learning, web scraping, and natural language processing. Cons: Bad fit for startups with few customers and companies that service very niche industries.
Which method you choose depends on your budget, internal marketing capabilities, and willingness to try new technologies. The next thing you want to do is experiment with a few methods and measure the results. Before you do that, you'll want to establish a baseline so that you know whether or not you are getting improvement. I'm surprised by how many companies do not know their baseline metrics before trying to measure a new lead source. Obviously, you'll have to know it in order to know which lead source is superior. Below are some ways you should considering measuring your current and new lead sources.
- Lead to MQL ratio. How many leads do you need to email or call to turn that lead into a Marketing Qualified Lead (MQL)? A marketing qualified lead (MQL) is a lead judged more likely to become a customer compared to other leads based on lead intelligence, often informed by closed-loop analytics. Typically if a lead has taken some small step toward you such as visiting your website or downloading a white paper, you can consider them an MQL.
- MQL to SQL ratio. How many MQLs do you need to generate an SQL? A sales qualified leads (SQL) is a lead that has authority to buy, needs your solution, and looking to make a decision in the near future.
- SQL to sales ratio. How many SQLs do you need to make a sale?
- Lead to sales ratio. This is the big enchilada. Use the other 3 ratios to build this one and then you can compare apples to apples. If you go for the lead source that generates the most MQLs but you can't close any of them, they are useless. So it's good to use the lead to sales ratio to control for those anomalies.
After you measure these ratios for your existing and new lead source, the only question that remains is which lead source performs better on these metrics? At that point, you can do some quick math using this Hubspot article and determine how many leads you need in order to make your numbers this year.
I wish you success and hope you crush your sales goals in 2016!