Sales targeting insight - giving your sales and marketing team direction by optimising customer and prospect contact strategies

Tech4T can increase your sales performance by identifying which new and existing customers to contact, when, why, how and how often!

Using your own operational data (customers, sales, appointments, enquiries/interests...), we can derive the insights needed to guide your sales and marketing effort toward the people more likely to give you high-value business!  We fill the customer knowledge gap and provide you with the intelligence in a format that is easy to deploy and will make (and save) you a significant amount of money.  

We can help you find out... 

• Who contributes the most revenue (customer value) - what they look like, their profile

• Who is likely to churn - defect to your competitors

• Who is more likely to purchase and in what order should they be contacted

• How their trading patterns vary over time and the impact of change

• Their true value to your company (lifetime value) and their profitability

• How they breakdown geographically

• How they can be grouped together (segmented)

• Who, when and why they should be contacted, and with what message, offer, etc.

• Which channel you should use - Sales visit, Telesales, Email, Direct mail, Conference, Door-to-door, Retail, Trade counter, Distributor, Agents... - when, and at what frequency

• Which customers should be allocated to which sales person, and are there gaps or is there overcrowding in sales coverage

• Based on customer profiles, what is the likely new business potential by Postcode, Zip code, etc., and where are the hot spots

• How do you best reach those new prospects, and which media are they more likely to respond to

 …and then use the insight for targeting and to enhance your customer proposition

Our process - a little insight as to how we work First we take a copy of your customer, sales and other relevant data going back over time, together with any additional profile or research data. If data needs cleansing, standardising or combining, we do this, and if sparse we can source and merge enrichment data and optionally implement a separate survey campaign.  For high volumes of data we use specialist FastStats technologies We then apply statistical analysis approaches - including analysing purchase recency, frequency and value (RFM) and using profiling and propensity models to identify the likelihood of an individual taking a specific course of action such as purchasing a particular product - and create a distinct number of unique database segments that can then be related to specific customer actions to win, keep, win-back and grow more high value customers. See also lapse prevention
	The starting point - no segmentation
Each segment differentiates a set of people who share similar characteristics. i.e. their profile, purchasing behaviour, spend (value), interests, etc.  One of the next steps is to repeat the exercise - again based on the snapshot of your sales data - but this time frozen as at one year ago (or an alternate timescale).  We can now see how customers have moved across segments over the 12 month period. i.e. spotting which high-value customers have lapsed, who have spent more (or less) as a whole - or across separate product groups, which customers are buying more or less frequently, etc.
	Statistically segmented and profiled customers

 

Sales targeting insight continued, click here