Sales teams throughout the world are taking advantage of data to turbocharge their revenue and boost ROI.
McKinsey recently reported that data-driven sales teams are 23 times more likely to acquire more customers whereas 62% of respondents to an IBM survey stated that data gave them a competitive advantage.
Despite the evident benefits of using data in business, it’s tricky to mobilise the benefits of data in a practical capacity.
Knowing where to start is difficult - what stats do you need to look at, and most importantly, how do you use the data to actually boost sales?
Here are 5 techniques for harnessing and using data to improve sales.
Customer relationship management software - CRMs - are invaluable to the sales process. Whilst CRMs were formerly at home in B2B industries where clients and contacts are innumerable but highly valuable, they’re now useful for B2C businesses too. The purpose of a CRM is to centralise customer leads and prospects across all of a business’s various touchpoints.
The first mistake businesses make with their CRM is failing to set it up properly. CRMs take some work to get them running smoothly. Rubbish in = rubbish out. For B2B businesses, contacts should be properly defined alongside all relevant information pertaining to their organisation, job role, authority, etc.
By properly organising B2B data, sales teams have peace of mind that their systems can be trusted and that key information is available in CRM when required, e.g. when on the phone to a lead, or when producing email marketing copy.
CRMs should also provide some indication of the customer’s status, e.g. are they a new contact or a repeat customer? Utilise CRMs to remind the sales team of when leads are going cold, i.e. they haven’t been contacted for a while. Ensure that the CRM is well maintained and is collecting data on:
- Deal status; how many deals are in progress, or pending
- Deal frequency; how often do you make deals
- Deal value; the value of deals and clients - higher value clients warrant more attention
- Performance by week, month, year, etc; you want to be able to analyse your sales performance across any given period
Qualitative customer data is an invaluable source of customer insight. The more intel businesses can collect on their customers, the better. Collecting qualitative data through web forms, customer feedback forms, surveys and quizzes is an ideal opportunity to really dig into your customer’s opinions on your brands/products.
Make sure that you provide customers with a means to feedback information if they want to, e.g. through a quiz or questionnaire. Incentives can be given for successful completion, e.g. prize draws.
Analyse this information to address customer’s pain points and smooth the sales process. You might find that there are one or two nagging issues that keep coming up, like a glitch that occurs at checkout or a display issue on Android phones - iron them out and you might notice an immediate boost in sales.
Segmenting customers is vital for businesses that are running ad or marketing campaigns, whether via email, social media or PPC. Without properly segmenting your audience, you won’t make the best of your marketing efforts. Whilst it’s entirely possible for a business to sell to both the over 50s and 18 to 25s, for example, you probably won’t want to send both demographics the same adverts or marketing material.
Advanced segmentation is possible with customer data platforms such as mParticle and Segment. Customers can be segmented using these tools and then ‘piped’ to Google Ads, email marketing tools or social media.
Segmentation at a lower level is possible by just looking through your CRM and using its built-in filters to group leads and contacts. For example, it might be wise to segment high-value clients in order to send them different email marketing copy.
Use segmentation to move away from a blunt ‘one size fits all’ approach. Treat different customers differently and sell to them using different sales techniques.
Selling is about knowing how to moderate the pressure you place on leads to take action on your products and offerings. Too much pressure and it’ll come across as too much of a hard sell, but too little and your customers will leave you, or your deals will rot.
Some CRMs, like Salesforce, have a ‘deal rot’ feature that alerts teams when leads are getting cold and could do with some input.
Otherwise, keep a close eye on when you last contacted your leads and ensure that you have a plan for recapturing their attention if things start sliding away.
Many CRMs allow teams to score leads by priority - use this data combined with your average deal cycles to visualise when you should re-target a lead or let them go. Priority leads should warrant the most work to keep interactions fresh and active, whether that be via email marketing, ad retargeting or booking phone appointments or face-to-face meetings.
By looking at past data, sales can be analysed with reference to a wider context or bigger picture.
Sales changes throughout time, both on a day-to-day basis and across weeks, months and years. A key example is the Christmas season which may signify a major uptick in activity for B2C businesses and a brief decline for B2B businesses until the new year kicks in again. Don’t assume that these sorts of trends apply to your business, though, look for them in your sales data yourself.
Use past sales data to identify peaks and troughs - look deeply at both your own sales data and data across the industry to try and explain why these fluctuations happen.
Sales teams should take into account not just their own internal sales data, but data from across their industry as a whole. So, whilst it’s important to study sales data internal to the sales team, it’s also important to look at the industry at large. Your sub-par sales in March might still exceed other teams in your industry, for example, so you’d be wasting time by looking too deeply into them
We live in the era of data but harnessing its benefits for business can seem like a minefield.
Always start with a quality CRM that is a natural fit for the business. Set it up properly and ensure customer data is structured, can be filtered and sorted easily.
By segmenting customers and leads and developing specific sales techniques for different customers, it’s possible to move away from a blunter ‘one size fits all’ sales technique.
Use historical data to contextualise strategies properly - don’t ignore clues from past sales periods or experiences.
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