The last few years has seen many vendors review and restructure their channel partner programmes to better meet the needs of their partners based on their actual/potential value and performance. This article examines how a new approach to optimising channel programme engagement and driving real differentiated end-user customer penetration can increase top line revenues and bottom-line profits.
Route-to-Market (RTM) mapping
An initial requirement is to ensure appropriate partner coverage at the macro level across different product, solution and sales objectives for different end customer segments. The RTM mapping process helps achieve this by plotting channel partners against two axes to give a visual representation of their make-up, ensuring the right quantity and quality of channel partners to meet customer needs for specific product or service propositions:
Developing channel personas
To better segment the business needs, motivations and behaviours of individuals within the channel partner organisation, vendors can also develop individual user profiles or 'personas'. These personas can help build a profile of those individuals that influence brand preference and product specification in end-customer solutions, as well as those who drive the different parts of the sales process.
By linking personas with company level segmentation, vendors can create a more personalised and relevant dialogue with the individual while ensuring a compelling proposition is being provided at the partner company level.
Creating a scoring model
The application of scoring models is proving effective to ascertain how the business is performing against key goals and can assist with decisions on how to better invest and manage channel partners. An example of its application analyses a Vendor's POS data over a set time frame and scores one channel partner's buying behaviour according to their:
- Recency: When did the partner last purchase?
- Frequency: How often do they purchase?
- Value: What is the makeup and value of purchases?
By allocating weighted scores to individual RFV segments and metrics, all channel partners can be ranked according to their combined RFV rating. The table illustrates the total number of partners by RFV score, highlights the percentage of total orders and total revenue for which they are responsible. Ongoing analysis provides reliable indicators of partner performance from which intelligent channel investment decisions can be made.
Applying predictive modelling
Going beyond scoring models, predictive modelling can drive further insight to efficiently acquire, grow and retain the right partners and also identify those which should not be invested in. It will determine, with accuracy, partners that have the propensity to take up specific offers and campaigns, or help achieve specific business goals. By eliminating the guesswork when targeting partner groups with more relevant marketing communications, ROI will rapidly increase through more efficient use of resources and reduced spending.
Channel partner segmentation models which aren't guided by structured 'data-fed' programmes are lacking the relevance to run effectively in today's marketplace. The complexity of end-user markets will continue to increase and so a more scientific approach to partner segmentation and communication management will be vital in ensuring the vendor has satisfied customers and successful channel partners well into the future.