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    Editor's Pick (1 - 4 of 8)
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    Mastering the Art and Science of Pricing

    Scott Gillies, Regional Director, APAC, Revionics

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    Scott Gillies, Regional Director, APAC, Revionics

    Retailers today face incredible market upheaval. Across the globe, shoppers are firmly in control, shopping 24/7 across all channels. The competitive environment is fierce as international giants, specialty on-line retailers, and aggressive startups all take on local retailers head-on. And in Australia, retail inflation has remained so far below the Consumer Price Index (CPI) for so long that the Reserve Bank of Australia conducted a special analysis and investigation, issuing a report last June that cited relatively soft commodity prices offsetting exchange rate depreciation in COGS and increasing retail competition, including pressure from international retailers aggressively seeking market share. With the so-called ‘Aldi effect’, Australian retailers are at a high risk of getting caught in a race to the bottom as they drown in price cuts while fighting for market share. Blindly responding to every competitive price change can end disastrously with unsustainably low margins and the demise of a profitable business model.

    Fortunately, proven data-driven analytics let retailers provide targeted pricing that responds to customer and competitive environments while preserving margins and the bottom line through the Responsive Merchandising Maturity Model – with distinct Crawl, Walk and Run phases.

    The Crawl Phase

    At the crawl phase, it’s critical to lay a solid foundation that delivers near-term results and helps to connect with customers, outperform the competition and succeed even in volatile times.

    1. Commit to data integrity: Fortunately, retailers today have unprecedented ability to collect meaningful and real-time competitive and customer data, and (as we’ll see in the Walk and Run phases) perform analytics that unlock clear and actionable insights. The foundational element is to clean up dirty data and implement processes to ensure data integrity going forward.

    2. Sharpen your price strategy: Moving from reactive to proactive means revisiting – and refocusing – your price strategy. Do you want to maximize profits or grow market share? Are you an Everyday Low Price provider or do you have a targeted high-low strategy? What is your desired price image? The answers in turn drive your Key Value Item (KVI) and price zone strategies.

    3. Implement automated, comprehensive competitive insights: Competition from all channels, from non-traditional as well as entrenched competitors, makes physical price-monitoring inadequate.

    To Meet Growth Targets, Retailers Must Offer Meaningful, Targeted Prices And Offers That Resonate With Customers

    Instead, retailers focused on responsive pricing turn to a targeted, scalable, automated shop process. The right solution provides insights into which products are important to your customers – and which are not.

    The Walk Phase

    Australian retailers can be forgiven if they sometimes feel as if they’ve fallen down a rabbit hole to a world where everything is topsy-turvy. While many macro-economic measures – including GDP and unemployment – are relatively robust, retail price wars are vicious and, as Reuters Australia recently reported, have even given rise to speculation about possible deflation.

    These ‘walk’ steps help retailers thrive through highly targeted, data-driven pricing decisions with updates that reflect real – and real-time – customer and competitive factors.

    1. Evolve rules-based pricing strategies: The days of going by ‘gut feel’ or past history are gone, and smart retailers set rules and parameters based on good data analytics, using both historical and current data. This also helps create much more granularity in their pricing, aligning with customer expectations on the items where it matters and recovering margin elsewhere.

    2. Implement more sophisticated KVI and zoning practices: With price tools and infrastructure that support business agility and machine-learning algorithms, retailers can get real-time insights across the competitive and consumer landscape and adjust the cadence of their KVI and price zone updates to respond with targeted and rapid price updates as markets shift.

    3. Automate competitive monitoring and workflows: Consumers shop 24/7 across all channels and banners, so your automated competitive monitoring should feed automated price update workflows (within pre-set parameters, of course) to speed your team’s ability to respond, freeing them up from manual tasks to:

    4. Conduct sophisticated forecasting and trending: With less time spent on repetitive tasks, teams can dive into sophisticated, easy-to-use software for modeling the impact of various market trends and price updates, making informed trade-offs between revenues, margins, and profits before they commit to a price change.

    The Run Phase

    The stark language of this comment jumped out at me in a recent Deloitte report, Global Powers of Retailing 2016: “The globalization of the Australian retail market is set to continue. Australian retailers, therefore face significant challenges in order to meet their growth targets in what is perhaps the most disrupted and competitive of all market sectors.”

    To meet growth targets, retailers must offer meaningful, targeted prices and offers that resonate with customers without needlessly sacrificing margins and profits. At this phase they typically deliver frequent, responsive price analysis and updates, science-based pricing and localization, category-level pricing strategies and trend analysis with both past and predictive analytics.

    Summarizing the above, it can be said that the Run-stage retailer discovers the deep rewards of continuing to refine, mature and shape the ways in which it applies science and analytics to business challenges. We often see price elasticity begin to be incorporated into business intelligence reports shared with other parts of the organization, measurement of price actions including price lift analysis, and perhaps most importantly, analysis of the contribution of price optimization (and of the pricing team itself) to revenue, margins, and volume performance metrics.

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