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For far too long, Sales Executives have wasted their time chasing dead leads that will never result in revenue. Sales Directors admit that prospecting has become increasingly difficult with consumer spending in steady decline and GDPR strangulating means of outreach. In a recent report, it was revealed that 79 per cent of all marketing leads are never converted into sales.
Sales and Marketing teams are being pressured to use Big Data and AI in order to deliver value to the business. The issue is that these teams don’t know how to properly harness the data that is available to them to derive genuine value from it. There are profound insights available to teams who are able to do this properly, but this is scarcely happening because of a lack of understanding amongst teams and businesses. Imagine an address book full of people you know should be buying from you, but the contacts’ names, phone numbers, email addresses and profile information are all jumbled up. High-quality data can be rendered futile if it is not easily accessible or presented in a useful way.
So, how can we unlock the power of that data to uncover opportunities, improve conversion rates and gain advantage over your competitors?
1. Know Your Customer
A Salesforce study found that 90 per cent of the average contact database is incomplete records. CRM systems are full of missing and duplicate records. Not having a clear view can be costly for the business – you don’t want to send collateral out to the same person three times because you have them on file under three slightly different variations of the same name.
As a first step you need to invest in creating a true Single Customer View (SCV.) I say this quickly, but this is possibly the hardest step.
2. Know more about that customer
There is only so much information that a Sales and Marketing team can collect on a customer. To truly understand them you need to enrich these records with external data. This might include learning more about the specificities of their industry, what they sell or how they’re performing relatively to their competitors. Looking at data such as website and buying activity can help businesses to understand their customers behaviour. Financial data like their profitability and liquidity can be indicative of what sort of things they are likely to invest it.
3. Is your best customer who you really think it is?
Every company has their flagship customer; those enterprise sales the CEO closed ten years ago when he started the company, but the best ones are really the ones who represent the majority. To understand who that is amongst your client base, you need to run analytics across all your data and find commonality. This allows you to understand the characteristics that make up the best customer for you. Are they high growth? Are they shrinking? Do they trade overseas? Are they all in the same industry?
4. Find more like them
It’s a logical step. Once you truly understand what characteristics your best customers have, you need to and find others like them. This is where the data gets exponentially bigger, because you need to understand all the businesses or people you can sell to.
5. Find the low hanging fruit
Now we understand our existing customers, and the ones we know we should be selling to, let’s get the low hanging fruit. By using a combination of internal and external data, we can see a network of customers that are in the same group structure or have the same owner. It’s much easier to open a call with, ‘Hey, we’re selling to your sister company’ or ‘we sold to you before at…’ than to make a completely cold call.
All of the above may seem laborious but the results are clear. It’s easier to sell to people that need what you’re selling. AI and Machine Learning technology are improving at an unimaginable rate so that all the above processes can be completely automated. Applying these techniques means teams can get qualified leads which they know they should be able to convert without wasting time prospecting or calling customers that they know don’t need them.