Articles in Category : customer engagement

The six steps to align marketing to customer journey in retail Amit Rohatgi April 24, 2019 Blog , customer engagement , customer experience , Customer Journey , Customer Life-cycle Marketing Plenty has been said about Journey Marketing and it is at the top of the list while evaluating marketing technology today. Rightly so. In a crowded retail landscape, customers have access to options and information from the comfort of their home, and just one below average touchpoint is enough to lo...

5 Mobile Marketing Tactics Your Restaurant Must Deploy This Quarter Manthan Editorial Desk April 16, 2019 Analytics , Blog , Campaign Management , Customer Analytics , Customer Data , customer engagement , Customer Insights , Customer Journey , Customer Life-cycle Marketing , Marketing Strategy , Personalization , Real-time Personalization , Restaurant Marketing , Restaurant Mobile Apps , Restaurants According to reports, orders placed via smartphones and mobile apps will become a $38 billion industry and makeup nearly 11% of all quick-service restaurant sales by 2020. In 2016, a Nielsen study showed us that millennials are the largest group of smartphone users, as well as the generation that di...

3 Things Every Retail Marketer Needs (and where your current marketing tools may be letting you down) Bhavna Sachar January 3, 2019 Blog , Campaign Management , Churn management , customer engagement , Customer Journey , Customer Life-cycle Marketing , Customer Marketing , Data-Driven Marketing , Mobile , Multichannel Marketing , next-best actions , Path-to-purchase , Personalization The last two decades have clearly demonstrated that the fundamentals of marketing remain the same What’s changed are the mechanisms used to achieve this. Pre-digitization, communications were one-way through mass media and only touchpoint was at the physical store...

Move Over Nostradamus: Prescriptive Analytics Takes Control of Customer Engagement Bhavna Sachar October 5, 2018 Blog , Customer Analytics , customer engagement , Next best offer , next-best actions , Prescriptive analytics Talk about how machine learning can predict and recommend based on various factors. In fashion, decisions such as color, size, fabric, design, style, preferred price range, where to promote are important. Similarly, in grocery, flavour, nutrition, convenience of use, dietary preferences, price point...