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5 Signs It’s Time to Switch Your Data Provider

 

If sales are flatlining, people are leaving and the boss is wondering what happened to growth, it’s time to switch your data provider.

 

Inbound was supposed to be the saviour of B2B customer acquisition with its promise of better-qualified leads. If sales and marketing teams review their conversion rates and costs, though, they will likely find it has been anything but.

The reason why is staring them in the face. The leads a digital marketing channel generates are typically drawn up in much the same way as they always have been. The industry has shifted to using the term digital, but it hasn’t shifted to a digital mindset.

If you buy data from a well-known provider, it will almost certainly be created with the same criteria used for the past few decades. Prospects are whittled down by the same Standard Industrial Classification (SIC) codes that places businesses into a variety of categories, based on their industry, company type, number of employees, and revenue.

With all the power that digital tools put into the hands of sales and marketing teams, they are still selecting companies based on classification criteria drawn up after the Second World War. These have had a couple of updates but they are mostly unfit for the modern economy. A good example is it has more classification for different types of shipwreck recovery companies than it does for software businesses.

Even when SIC codes are not used directly, prospect audiences are still usually compiled with the same mentality of judging a business’s likelihood to buy based on what industry it operates in, how much revenue it earns, and how many people it employs. 

This 84-year-old classification system is only half the story, though. 

 

Why size really doesn’t matter, neither do categories

 

To get the real benefit from digital (and other marketing) channels, companies need to build a more nuanced picture of their ideal customer profiles (ICP). They need to understand which digital signals they should look out for when determining if a company is a good fit for what they are selling. That goes way beyond just the category of business they fall into, according to their size and number of employees.

To begin with, the actual classification of a business is rarely helpful because they do not sum up all that a company does. Your ideal customer might be a hotel or a B&B. Using SIC codes or industry, you will get a list of companies in those sectors but will also miss restaurants and pubs which are classified by their primary business but also have rooms to let. 

When marketing teams engage a data provider that can think beyond outdated classification and over-simplified targeting criteria and take a better-informed view of an SME, opportunities start to open up.

Savvy marketers can look at their sweet spot by analysing their CRM system to see which businesses have historically proven to be a particularly good fit. Similar businesses that fit that criteria can then be picked out by detecting the digital signals they give out, rather than how they describe themselves on Companies House. But to do that, you’ll need access to a different kind of data.

 

Look for digital signals, not classifications

 

When you begin to look at the business in detail and get down to what it does, how it is set up, new opportunities start to open up. You can see where it has offices, whether those offices are shared or rented, whether it is an early adopter or a laggard of the latest technology, or, does it take digital payments, how many vehicles it leases.

These insights will help businesses in different ways, depending on what they are selling. If you take the example of say, a utility company, a business might appear to be a good fit to a conventional data provider because it employs a lot of people and so is likely to be a heavy user of electricity. However, that really doesn’t matter if it is in a serviced office where the landlord takes care of utility contracts. It is clearly a total waste of time to target them. And yet, everyday sales reps are contacting businesses who are not in-market for what they sell.

The solution is for a business to analyse its CRM system to gain a better understanding of where its sweet spot for customers lies — which type of companies it is most successful in selling to. 

A case in point is a well-known B2B transportation company Growth Intelligence works with. It has a particular sweet spot with taking company staff to airports. Now, a traditional data provider might think only a certain type of company sends its people overseas frequently, and then come up with SIC codes, revenue, and employee numbers that match the ill-considered assumption. 

We are able to see where a business is and, crucially, where its other offices are. If it has international offices, that is a very strong signal they are a good match for a business that needs airport runs. It might only have a handful of staff but if they have international offices they send people to, they are a far better prospect than a large company which rarely needs a taxi to the airport.

If another company were selling a modern payment technology to restaurants and cafes, it would traditionally just get an exhaustive list of companies that fit that SIC code. However, it makes far more sense to see which ones are forward-thinking, which have websites, which have invested in cloud technology, and which allow bookings online. You will never get that from a standard SIC code, but you can from AI technology that picks up digital signals that reveal the culture of a company, not just how it classifies itself on Companies House.

These are just a couple of examples of how looking at digital signals is far more helpful in defining a company’s likely needs than adding companies to a list based solely on sector and size.

The challenge is, sales and marketing leaders may think that this is simply how it has to be, that there is no alternative than going through long lists of barely qualified names and numbers to call. However, there are a few signs to look out for that will signal it is time to use a data provider that uses deeper intelligence, not just a slightly jazzed-up version of the Yellow Pages.

 

1. It’s becoming harder to generate leads

 

Conversion rates are low because you are targeting audiences of businesses based on assumptions of your ICP (sector, revenue, employees) rather than more revealing data signals which suggest the goods and services they are likely to be a good fit for. Our analysis of millions of prospecting attempts reveals that often over 80% of the activity is focused on bad-fit prospects.

 

2. It’s becoming more expensive

 

Because conversion rates are low and decrease over time as more of the good-fit prospects are gradually snapped up, customer acquisition costs increase. 

 

3. Your people are leaving

 

Sales teams expect a level of staff churn but when people are struggling to make their commission targets because lead conversion rates have dropped, the number of people leaving the organisation will go up.

 

4. Your target audiences are disjointed 

 

Many data providers will provide lead lists that are fit for a specific marketing channel e.g. telesales. If you want to ensure that all your channels target the same companies you need to ensure your audience lists are interoperable.

 

5. You are considering a lead generation agency

 

If any of the above apply, you might be tempted to bring in a lead generation company. However, this is effectively paying a third party to compete with you for the same customers. What a business needs is a partner powering its sales and marketing campaigns with better-targeted audiences, not a subsidised competitor.

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